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  • 1.
    Aronsson, Martin
    et al.
    SICS.
    Bohlin, Markus
    SICS.
    Doganay, Kivanc
    SICS.
    Holst, Anders
    SICS.
    An Integrated Adaptive Maintenance Concept2010Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a novel maintenance concept based on condition monitoring and dynamic maintenance packaging, by showing how to connect the information flow from low-level sensors to high-level operations and planning under uncertainty. Today, condition-based maintenance systems are focused on data collection and custom-made rule based systems for data analysis. In many cases, the focus is on measuring "everything" without considering how to use the measurements. In addition, the measurements are often noisy and the future is unpredictable which adds a lot of uncertainty. As a consequence, maintenance is often planned in advance and not replanned when new condition data is available. This often reduces the benefits of condition monitoring. The concept is based on the combination of robust, dynamically adapted maintenance optimization and statistical data analysis where the uncertainty is considered. This approach ties together low-level data acquisition and high-level planning and optimization. The concept has been illustrated in a context of rail vehicle maintenance, where measurements of brake pad and pantograph contact strip wear is used to predict the near future condition, and plan the maintenance activities.

  • 2.
    Aronsson, Martin
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Doganay, Kivanc
    RISE, Swedish ICT, SICS.
    Holst, Anders
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Kjellqvist, Tommy
    Östlund, Stefan
    An Integrated Adaptive Maintenance Concept2010Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a novel maintenance concept based on condition monitoring and dynamic maintenance packaging, by showing how to connect the information flow from low-level sensors to high-level operations and planning under uncertainty. Today, condition-based maintenance systems are focused on data collection and custom-made rule based systems for data analysis. In many cases, the focus is on measuring "everything" without considering how to use the measurements. In addition, the measurements are often noisy and the future is unpredictable which adds a lot of uncertainty. As a consequence, maintenance is often planned in advance and not replanned when new condition data is available. This often reduces the benefits of condition monitoring. The concept is based on the combination of robust, dynamically adapted maintenance optimization and statistical data analysis where the uncertainty is considered. This approach ties together low-level data acquisition and high-level planning and optimization. The concept has been illustrated in a context of rail vehicle maintenance, where measurements of brake pad and pantograph contact strip wear is used to predict the near future condition, and plan the maintenance activities.

  • 3.
    Aronsson, Martin
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    MILP formulations of cumulative constraints for railway scheduling - A comparative study2009In: The Proceedings of the 9th Workshop on Algorithmic Methods and Models for Optimization of Railways (ATMOS), Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany , 2009, 13Conference paper (Refereed)
    Abstract [en]

    This paper introduces two Mixed Integer Linear Programming (MILP) models for railway traffic planning using a cumulative scheduling constraint and associated pre-processing filters. We compare standard solver performance for these models on three sets of problems from the railway domain and for two of them, where tasks have unitary resource consumption, we also compare them with two more conventional models. In the experiments, the solver performance of one of the cumulative models is clearly the best and is also shown to scale very well for a large scale practical railway scheduling problem.

  • 4.
    Aronsson, Martin
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Mixed integer-linear formulations of cumulative scheduling constraints - A comparative study2007Report (Other academic)
    Abstract [en]

    This paper introduces two MILP models for the cumulative scheduling constraint and associated pre-processing filters. We compare standard solver performance for these models on three sets of problems and for two of them, where tasks have unitary resource consumption, we also compare them with two models based on a geometric placement constraint. In the experiments, the solver performance of one of the cumulative models, is clearly the best and is also shown to scale very well for a large scale industrial transportation scheduling problem.

  • 5.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    A Local Search System for Solving Constraint Problems of Declarative Graph-Based Global Constraints2004In: Proceedings of the 15th International Conference on Applications of Declarative Programming and Knowledge Management, 2004, 1Conference paper (Refereed)
    Abstract [en]

    In this paper we present a local search constraint solver in which constraints are expressed using cost functions on graph structures of filter constraints of equal type. A similar theoretical approach has previously been used to model a large number of complex global constraints, which motivates the use of such a model in practice. In a local search context, we view global constraints as complex cost functions, encapsulating the structure of the constraints using a graph of variables, values and filter constraints. This representation gives us a declarative model, which can also be used to efficiently compute a cost as well as conflict levels of the variables in the constraints. We have implemented these ideas in a compositional C++ framework called Composer, which can be used to solve systems of graph-based constraints. We demonstrate the usability of this approach on several well-known global constraints, and show by experimental results on two problems that an approach using a graph basis for global constraint modeling is not only possible in practice, but also competitive with existing constraint-based local search systems.

  • 6.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    A Local Search System for Solving Constraint Problems of Declarative Graph-Based Global Constraints2005In: Applications of Declarative Programming and Knowledge Management: 15th International Conference on Applications of Declarative Programming and Knowledge Management, INAP 2004, and 18th Workshop on Logic Programming: Revised Selected Papers, Springer , 2005, 1, , p. 308p. 166-184Conference paper (Refereed)
    Abstract [en]

    In this paper we present a local search constraint solver in which constraints are expressed using cost functions on graph structures of filter constraints of equal type. A similar theoretical approach has previously been used to model a large number of complex global constraints, which motivates the use of such a model in practice. In a local search context, we view global constraints as complex cost functions, encapsulating the structure of the constraints using a graph of variables, values and filter constraints. This representation gives us a declarative model, which can also be used to efficiently compute a cost as well as conflict levels of the variables in the constraints. We have implemented these ideas in a compositional C++ framework called Composer, which can be used to solve systems of graph-based constraints. We demonstrate the usability of this approach on several well-known global constraints, and show by experimental results on two problems that an approach using a graph basis for global constraint modeling is not only possible in practice, but also competitive with existing constraint-based local search systems.

  • 7.
    Bohlin, Markus
    Mälardalen University, School of Innovation, Design and Engineering.
    A Study of Combinatorial Optimization Problems in Industrial Computer Systems2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A combinatorial optimization problem is an optimization problem where the number of possible solutions are finite and grow combinatorially with the problem size. Combinatorial problems exist everywhere in industrial systems. This thesis focuses on solving three such problems which arise within two different areas where industrial computer systems are often used. Within embedded systems and real-time systems, we investigate the problems of allocating stack memory for an system where a shared stacks may be used, and of estimating the highest response time of a task in a system of industrial complexity. We propose a number of different algorithms to compute safe upper bounds on run-time stack usage whenever the system supports stack sharing. The algorithms have in common that they can exploit commonly-available information regarding timing behaviour of the tasks in the system. Given upper bounds on the individual stack usage of the tasks, it is possible to estimate the worst-case stack behaviour by analysing the possible and impossible preemption patterns. Using relations on offset and precedences, we form a preemption graph, which is further analysed to find safe upper-bounds on the maximal preemptions chain in the system. For the special case where all tasks exist in a single static schedule and share a single stack, we propose a polynomial algorithm to solve the problem. For generalizations of this problem, we propose an exact branch-and-bound algorithm for smaller problems and a polynomial heuristic algorithm for cases where the branch-and-bound algorithm fails to find a solution in reasonable time. All algorithms are evaluated in comprehensive experimental studies. The polynomial algorithm is implemented and shipped in the developer tool set for a commercial real-time operating system, Rubus OS. The second problem we study in the thesis is how to estimate the highest response time of a specified task in a complex industrial real-time system. The response-time analysis is done using a best-effort approach, where a detailed model of the system is simulated on input constructed using a local search procedure. In an evaluation on three different systems we can see that the new algorithm were able to produce higher response times much faster than what has previously been possible. Since the analysis is based on simulation and measurement, the results are not safe in the sense that they are always higher or equal to the true response time of the system. The value of the method lies instead in that it makes it possible to analyse complex industrial systems which cannot be analysed accurately using existing safe approaches. The third problem is in the area of maintenance planning, and focus on how to dynamically plan maintenance for industrial systems. Within this area we have focused on industrial gas turbines and rail vehicles.  We have developed algorithms and a planning tool which can be used to plan maintenance for gas turbines and other stationary machinery. In such problems, it is often the case that performing several maintenance actions at the same time is beneficial, since many of these jobs can be done in parallel, which reduces the total downtime of the unit. The core of the problem is therefore how to (or how not to) group maintenance activities so that a composite cost due to spare parts, labor and loss of production due to downtime is minimized. We allow each machine to have individual schedules for each component in the system. For rail vehicles, we have evaluated the effect of replanning maintenance in the case where the component maintenance deadline is set to reflect a maximum risk of breakdown in a Gaussian failure distribution. In such a model, we show by simulation that replanning of maintenance can reduce the number of maintenance stops when the variance and expected value of the distribution are increased.  For the gas turbine maintenance planning problem, we have evaluated the planning software on a real-world scenario from the oil and gas industry and compared it to the solutions obtained from a commercial integer programming solver. It is estimated that the availability increase from using our planning software is between 0.5 to 1.0 %, which is substantial considering that availability is currently already at 97-98 %.

  • 8.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    A Study of Combinatorial Optimization Problems in Industrial Computer Systems2009Doctoral thesis, monograph (Other academic)
    Abstract [en]

    A combinatorial optimization problem is an optimization problem where the number of possible solutions are finite and grow combinatorially with the problem size. Combinatorial problems exist everywhere in industrial systems. This thesis focuses on solving three such problems which arise within two different areas where industrial computer systems are often used. Within embedded systems and real-time systems, we investigate the problems of allocating stack memory for an system where a shared stacks may be used, and of estimating the highest response time of a task in a system of industrial complexity. We propose a number of different algorithms to compute safe upper bounds on run-time stack usage whenever the system supports stack sharing. The algorithms have in common that they can exploit commonly-available information regarding timing behaviour of the tasks in the system. Given upper bounds on the individual stack usage of the tasks, it is possible to estimate the worst-case stack behaviour by analysing the possible and impossible preemption patterns. Using relations on offset and precedences, we form a preemption graph, which is further analysed to find safe upper-bounds on the maximal preemptions chain in the system. For the special case where all tasks exist in a single static schedule and share a single stack, we propose a polynomial algorithm to solve the problem. For generalizations of this problem, we propose an exact branch-and-bound algorithm for smaller problems and a polynomial heuristic algorithm for cases where the branch-and-bound algorithm fails to find a solution in reasonable time. All algorithms are evaluated in comprehensive experimental studies. The polynomial algorithm is implemented and shipped in the developer tool set for a commercial real-time operating system, Rubus OS. The second problem we study in the thesis is how to estimate the highest response time of a specified task in a complex industrial real-time system. The response-time analysis is done using a best-effort approach, where a detailed model of the system is simulated on input constructed using a local search procedure. In an evaluation on three different systems we can see that the new algorithm were able to produce higher response times much faster than what has previously been possible. Since the analysis is based on simulation and measurement, the results are not safe in the sense that they are always higher or equal to the true response time of the system. The value of the method lies instead in that it makes it possible to analyse complex industrial systems which cannot be analysed accurately using existing safe approaches. The third problem is in the area of maintenance planning, and focus on how to dynamically plan maintenance for industrial systems. Within this area we have focused on industrial gas turbines and rail vehicles. We have developed algorithms and a planning tool which can be used to plan maintenance for gas turbines and other stationary machinery. In such problems, it is often the case that performing several maintenance actions at the same time is beneficial, since many of these jobs can be done in parallel, which reduces the total downtime of the unit. The core of the problem is therefore how to (or how not to) group maintenance activities so that a composite cost due to spare parts, labor and loss of production due to downtime is minimized. We allow each machine to have individual schedules for each component in the system. For rail vehicles, we have evaluated the effect of replanning maintenance in the case where the component maintenance deadline is set to reflect a maximum risk of breakdown in a Gaussian failure distribution. In such a model, we show by simulation that replanning of maintenance can reduce the number of maintenance stops when the variance and expected value of the distribution are increased. For the gas turbine maintenance planning problem, we have evaluated the planning software on a real-world scenario from the oil and gas industry and compared it to the solutions obtained from a commercial integer programming solver. It is estimated that the availability increase from using our planning software is between 0.5 to 1.0 %, which is substantial considering that availability is currently already at 97-98 %.

  • 9.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Constraint satisfaction by local search2002Report (Other academic)
    Abstract [en]

    The constraint satisfaction problem and its derivate, the propositional satisfiability problem (SAT), are fundamental problems in computing theory and mathematical logic. SAT was the first proved NP-complete problem, and although complete algorithms have been dominating the constraint satisfaction field, incomplete approaches based on local search has been successful the last ten years. In this report we give a general framework for constraint satisfaction using local search as well as an different techniques to improve this basic local search framework. We also give an overview of algorithms for problems of constraint satisfaction and optimization using heuristics, and discuss hybrid methods that combine complete methods for constraint satisfaction with local search techniques.

  • 10.
    Bohlin, Markus
    Mälardalen University, Department of Computer Science and Engineering.
    Design and implementation of a graph-based constraint model for local search2004Licentiate thesis, comprehensive summary (Other scientific)
  • 11.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Bruce, Lars
    Redesign of the Oz Compiler2002Report (Other academic)
    Abstract [en]

    This master of science thesis describes a new design and its implementation for an Oz compiler. The project is based on the existing Oz compiler. The new compiler is designed more modular, with separate software components that can be replaced and modified locally. A prototype has been implemented, but further development is necessary. We give an overview of the language Oz, its features and the underlying calculus. The features of Oz regarding object orientation, functional programming, logic and constraint programming are also discussed. The liveness analysis and register allocation problems in general and regarding Oz specific compilers are analyzed, together with current and future optimizations suitable for the Mozart platform. The design of the new compiler and information about the old one is presented, and future work regarding the compiler, optimizations, and analysis phases is discussed. Appendices describing the interfaces between the phases of the compiler is included, together with documentation regarding the internal code formats used.

  • 12.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Dahms, Florian
    Flier, Holger
    Gestrelius, Sara
    RISE, Swedish ICT, SICS.
    Optimal Freight Train Classification using Column Generation2012Conference paper (Refereed)
  • 13.
    Bohlin, Markus
    et al.
    Swedish Institute of Computer Science, Sweden.
    Dahms, FlorianRWTH Aachen, Chair of Operations Research, Germany.Flier, HolgerETH Zürich, Institute of Theoretical Computer Science, Switzerland.Sara, GestreliusSwedish Institute of Computer Science, Sweden.
    Optimal Freight Train Classification using Column Generation2012Collection (editor) (Refereed)
  • 14.
    Bohlin, Markus
    et al.
    Swedish Institute of Computer Science, SICS.
    Doganay, Kivanc
    Swedish Institute of Computer Science, SICS.
    Kreuger, P.
    Swedish Institute of Computer Science, SICS.
    Steinert, R.
    KTH.
    Wärja, Mathias
    Siemens Industrial Turbomachinery AB.
    Searching for Gas Turbine Maintenance Schedules2010In: The AI Magazine, ISSN 0738-4602, Vol. 31, no 1, p. 21-36Article in journal (Refereed)
    Abstract [en]

    Preventive maintenance schedules occurring in industry are often suboptimal with regard to maintenance coal-location, loss-of-production costs and availability. We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines, with the goal of reducing the direct maintenance costs and the often costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that the feasibility version is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using integer programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, the use of our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days by 12%. Compared to a integer programming approach, our algorithm is not optimal, but is much faster and produces results which are useful in practice. Our test results and SIT AB’s estimates based< on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals.

  • 15.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Doganay, Kivanc
    RISE, Swedish ICT, SICS.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Scheduling Gas Turbine Maintenance Based on Condition Data2009In: Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference, 2009, 6Conference paper (Refereed)
  • 16.
    Bohlin, Markus
    et al.
    Swedish Institute of Computer Science, SICS.
    Doganay, Kivanc
    Swedish Institute of Computer Science, SICS.
    Kreuger, Per
    Swedish Institute of Computer Science, SICS.
    Steinert, Rebecca
    Swedish Institute of Computer Science, SICS.
    Wärja, Mathias
    Siemens Industrial Turbomachinery AB.
    A Tool for Gas Turbine Maintenance Scheduling2009In: Proceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09, 2009, p. 9-16Conference paper (Refereed)
    Abstract [en]

    We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines. The tool is used to plan the maintenance for turbines manufactured and maintained by Siemens Industrial Turbomachinery AB (SIT AB) with the goal to reduce the direct maintenance costs and the often very costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that feasibility in it is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes, and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using mixed integer linear programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, using our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days with 12%. Compared to a mixed integer programming approach, our algorithm not optimal, but is orders of magnitude faster and produces results which are useful in practice. Our test results and SIT AB's estimates based on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals

  • 17.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Doganay, Kivanc
    RISE, Swedish ICT, SICS.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Steinert, Rebecca
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Wärja, Mathias
    A Tool for Gas Turbine Maintenance Scheduling2009In: Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence (IAAI'09), IEEE Computer Society , 2009, 20Conference paper (Refereed)
    Abstract [en]

    We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines. The tool is used to plan the maintenance for turbines manufactured and maintained by Siemens Industrial Turbomachinery AB (SIT AB) with the goal to reduce the direct maintenance costs and the often very costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that feasibility in it is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes, and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using mixed integer linear programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, using our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days with 12%. Compared to a mixed integer programming approach, our algorithm not optimal, but is orders of magnitude faster and produces results which are useful in practice. Our test results and SIT AB’s estimates based on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals.

  • 18.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Doganay, Kivanc
    RISE, Swedish ICT, SICS.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Steinert, Rebecca
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Wärja, Mathias
    Searching for Gas Turbine Maintenance Schedules2010In: AI Magazine, Vol. 31, no 1, p. 21-36Article in journal (Refereed)
    Abstract [en]

    Preventive maintenance schedules occurring in industry are often suboptimal with regard to maintenance coal-location, loss-of-production costs and availability. We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines, with the goal of reducing the direct maintenance costs and the often costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that the feasibility version is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using integer programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, the use of our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days by 12%. Compared to a integer programming approach, our algorithm is not optimal, but is much faster and produces results which are useful in practice. Our test results and SIT AB’s estimates based< on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals.

  • 19.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Ekman, Jan
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Holst, Anders
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    The opportunistic replacement and inspection problem for components with a stochastic life time2011Report (Other academic)
    Abstract [en]

    The problem of finding efficient maintenance and inspection schemes in the case of components with a stochastic life time is studied and a mixed integer programming solution is proposed. The problem is compared with the two simpler problems of which the studied problem is a generalisation: The opportunistic replacement problem, assuming components with a deterministic life time and The opportunistic replacement problem for components with a stochastic life time, for maintenance schemes without inspections.

  • 20. Bohlin, Markus
    et al.
    Flier, Holger
    Optimal Freight Train Classification using Column Generation2012In: 12th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, September 13, 2012, Ljubljana, Slovenia, 2012, p. 10-22Conference paper (Refereed)
  • 21.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Flier, Holger
    Maue, Jens
    Matúš, Mihalák
    Track Allocation in Freight-Train Classification with Mixed Tracks2011Conference paper (Refereed)
    Abstract [en]

    We consider the process of forming outbound trains from cars of inbound trains at rail-freight hump yards. Given the arrival and departure times as well as the composition of the trains, we study the problem of allocating classification tracks to outbound trains such that every outbound train can be built on a separate classification track. We observe that the core problem can be formulated as a special list coloring problem in interval graphs, which is known to be NP-complete. We focus on an extension where individual cars of different trains can temporarily be stored on a special subset of the tracks. This problem induces several new variants of the list-coloring problem, in which the given intervals can be shortened by cutting off a prefix of the interval. We show that in case of uniform and sufficient track lengths, the corresponding coloring problem can be solved in polynomial time, if the goal is to minimize the total cost associated with cutting off prefixes of the intervals. Based on these results, we devise two heuristics as well as an integer program to tackle the problem. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangård hump yard in Sweden. Planning over horizons of seven days, we obtain feasible solutions from the integer program in all scenarios, and from the heuristics in most scenarios.

  • 22.
    Bohlin, Markus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering. SICS, Sweden.
    Flier, Holger
    Mälardalen University, School of Innovation, Design and Engineering. ETH, Suisse.
    Maue, Jens
    ETH, Suisse.
    Mihalák, Matúš
    Mälardalen University, School of Innovation, Design and Engineering. ETH, Suisse.
    Hump Yard Track Allocation with Temporary Car Storage2011In: 4th International Seminar on Railway Operations Modelling and Analysis, 2011Conference paper (Refereed)
    Abstract [en]

    In rail freight operation, freight cars need to be separated and reformed into new trains at hump yards. The classification procedure is complex and hump yards constitute bottlenecks in the rail freight network, often causing outbound trains to be delayed. One of the problems is that planning for the allocation of tracks at hump yards is difficult, given that the planner has limited resources (tracks, shunting engines, etc.) and needs to foresee the future capacity requirements when planning for the current inbound trains. In this paper, we consider the problem of allocating classification tracks in a rail freight hump yard for arriving and departing trains with predetermined arrival and departure times. The core problem can be formulated as a special list coloring problem. We focus on an extension where individual cars can temporarily be stored on a special subset of the tracks. An extension where individual cars can temporarily be stored on a special subset of the tracks is also considered. We model the problem using mixed integer programming, and also propose several heuristics that can quickly give feasible track allocations. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangard hump yard in Sweden. Planning over horizons over two to four days, we obtain feasible solutions from both the exact and heuristic approaches that allow all outgoing trains to leave on time.

  • 23.
    Bohlin, Markus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Flier, Holger
    ETH Zürich, Institute of Theoretical Computer Science, Switzerland.
    Maue, Jens
    ETH Zürich, Institute of Theoretical Computer Science, Switzerland.
    Mihalák, Matúš
    ETH Zürich, Institute of Theoretical Computer Science, Switzerland.
    Track Allocation in Freight-Train Classification with Mixed Tracks2011In: OpenAccess Series in Informatics, Volume 20, 2011, 2011, p. 38-51Conference paper (Refereed)
    Abstract [en]

    We consider the process of forming outbound trains from cars of inbound trains at rail-freight hump yards. Given the arrival and departure times as well as the composition of the trains, we study the problem of allocating classification tracks to outbound trains such that every outbound train can be built on a separate classification track. We observe that the core problem can be formulated as a special list coloring problem in interval graphs, which is known to be NP-complete. We focus on an extension where individual cars of different trains can temporarily be stored on a special subset of the tracks. This problem induces several new variants of the list-coloring problem, in which the given intervals can be shortened by cutting off a prefix of the interval. We show that in case of uniform and sufficient track lengths, the corresponding coloring problem can be solved in polynomial time, if the goal is to minimize the total cost associated with cutting off prefixes of the intervals. Based on these results, we devise two heuristics as well as an integer program to tackle the problem. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangard hump yard in Sweden. Planning over horizons of seven days, we obtain feasible solutions from the integer program in all scenarios, and from the heuristics in most scenarios.

  • 24.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Flier, Holger
    Maue, Jens
    Mihalák, Matúš
    Hump Yard Track Allocation with Temporary Car Storage2011Conference paper (Refereed)
    Abstract [en]

    In rail freight operation, freight cars need to be separated and reformed into new trains at hump yards. The classification procedure is complex and hump yards constitute bottlenecks in the rail freight network, often causing outbound trains to be delayed. One of the problems is that planning for the allocation of tracks at hump yards is difficult, given that the planner has limited resources (tracks, shunting engines, etc.) and needs to foresee the future capacity requirements when planning for the current inbound trains. In this paper, we consider the problem of allocating classification tracks in a rail freight hump yard for arriving and departing trains with predetermined arrival and departure times. The core problem can be formulated as a special list coloring problem. We focus on an extension where individual cars can temporarily be stored on a special subset of the tracks. An extension where individual cars can temporarily be stored on a special subset of the tracks is also considered. We model the problem using mixed integer programming, and also propose several heuristics that can quickly give feasible track allocations. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangård hump yard in Sweden. Planning over horizons over two to four days, we obtain feasible solutions from both the exact and heuristic approaches that allow all outgoing trains to leave on time.

  • 25.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Flier, Holger
    Maue, Jens
    Mihalák, Matúš
    Hump Yard Track Allocation with Temporary Car Storage2010Report (Other academic)
    Abstract [en]

    In rail freight operation, freight cars need to be separated and reformed into new trains at hump yards. The classification procedure is complex and time consuming, and hump yards often constitute bottlenecks in the rail freight network. One of the problems is that planning for the allocation of tracks at hump yards is difficult, given that the planner has limited resources (tracks, shunting engines, etc.) and needs to foresee the future capacity requirements when planning for the current inbound trains. In this paper, we consider the problem of allocating classification tracks in a rail freight hump yard for arriving and departing trains. Arrival and departure times are predetermined and may originate in timetables or estimated arrival and departure times (in case of disturbances in the rail system). The core problem can be formulated as a special list coloring problem. We focus on an extension where individual cars can temporarily be stored on a special subset of the tracks. We model the problem using mixed integer programming, and also propose several heuristics that can quickly give feasible track allocations. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangård hump yard in Sweden. Planning over horizons over two to four days, we obtain feasible solutions from both the exact and heuristic approaches that allow all outgoing trains to leave on time.

  • 26.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Forsgren, Malin
    Utvärdering av simulerat dynamiskt underhåll för spårbundna fordon2008Report (Other academic)
    Abstract [sv]

    Rapporten beskriver ett antal provkörningar av TIMM-demonstratorn utförda för att undersöka hur antalet besök i verkstaden varierar givet en förväntad underhållsvinst från CBM. TIMM-demonstratorn är en programvara framtagen för att under drift planera in underhållsbesök för ett antal simulerade fordon i spårtrafik, där underhållsbehovet styrs av dynamiskt varierande mätvärden på fordonen.

  • 27.
    Bohlin, Markus
    et al.
    SICS.
    Forsgren, Malin
    SICS.
    Holst, Anders
    SICS.
    Levin, Björn
    SICS.
    Aronsson, Martin
    SICS.
    Steinert, Rebecca
    SICS.
    Reducing vehicle maintenance using condition monitoring and dynamic planning2008In: In Proc. of the 4th IET Intl. Conf. on Railway Condition Monitoring (RCM’08), June 2008, 2008, Vol. 2216Conference paper (Refereed)
  • 28.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Forsgren, Malin
    RISE - Research Institutes of Sweden, ICT, SICS.
    Holst, Anders
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Levin, Björn
    RISE - Research Institutes of Sweden, ICT, SICS.
    Aronsson, Martin
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Steinert, Rebecca
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Reducing vehicle maintenance using condition monitoring and dynamic planning2008In: Proceedings of the 4th IET International Conference on Railway Condition Monitoring (RCM'08), 2008, 1Conference paper (Refereed)
  • 29.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Gestrelius, Sara
    RISE, Swedish ICT, SICS.
    Optimerad rangering: slutsatser och resultat från projektet RANPLAN2013Report (Other academic)
    Abstract [sv]

    Sammanfattning Rapporten innehåller kortfattade slutsatser och resultat från en studie genomförd i projektet RANPLAN, som har utförts av SICS Swedish ICT AB på uppdrag av Trafikverket under åren 2010-2013. Fokus är på Hallsbergs rangerbangård, men resultaten är tillämpbara även på andra rangerbangårdar med vall. Datorkörningar visar att blanddragen kan öka kapaciteten på rangerbangårdar väsentligt, mätt i antalet samtidiga tåg som kan hanteras, till en kostnad av en ökad mängd vagnsrörelser. I en jämförande datorstudie av simulering och optimering framgick också att de optimala planerna var betydligt effektivare, mätt i antalet vagnsrörelser, än de simulerade planerna. Resultaten pekar tydligt på att datorstödd optimering av planeringsprocessen för rangerbangårdar både är praktiskt möjligt och kan ge stora effektivitetsvinster.

  • 30.
    Bohlin, Markus
    et al.
    SICS Swedish ICT AB, Sweden.
    Gestrelius, Sara
    SICS Swedish ICT AB, Sweden.
    Dahms, Florian
    RWTH Aachen University, Germany.
    Mihalák, Matúš
    ETH Zürich, Switzerland.
    Flier, Holger
    ETH Zürich, Switzerland.
    Optimization Methods for Multistage Freight Train Formation2015In: Transportation Science, ISSN 0041-1655, E-ISSN 1526-5447, Vol. 50, no 3, p. 823-840Article in journal (Refereed)
  • 31.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Gestrelius, Sara
    RISE, Swedish ICT, SICS.
    Dahms, Florian
    RWTH Aachen University, Germany.
    Mihalák, Matúš
    ETH Zurich, Switzerland.
    Flier, Holger
    ETH Zurich, Switzerland.
    Optimization Methods for Multistage Freight Train Formation2015In: Transportation Science, ISSN 0041-1655, E-ISSN 1526-5447, Vol. 50, no 3, p. 823-840Article in journal (Refereed)
    Abstract [en]

    This paper considers mathematical optimization for the multistage train formation problem, which at the core is the allocation of classification yard formation tracks to outbound freight trains, subject to realistic constraints on train scheduling, arrival and departure timeliness, and track capacity. The problem formulation allows the temporary storage of freight cars on a dedicated mixed-usage track. This real-world practice increases the capacity of the yard, measured in the number of simultaneous trains that can be successfully handled. Two optimization models are proposed and evaluated for the multistage train formation problem. The first one is a column-based integer programming model, which is solved using branch and price. The second model is a simplified reformulation of the first model as an arc-indexed integer linear program, which has the same linear programming relaxation as the first model. Both models are adapted for rolling horizon planning and evaluated on a five-month historical data set from the largest freight yard in Scandinavia. From this data set, 784 instances of different types and lengths, spanning from two to five days, were created. In contrast to earlier approaches, all instances could be solved to optimality using the two models. In the experiments, the arc-indexed model proved optimality on average twice as fast as the column-based model for the independent instances, and three times faster for the rolling horizon instances. For the arc-indexed model, the average solution time for a reasonably sized planning horizon of three days was 16 seconds. Regardless of size, no instance took longer than eight minutes to be solved. The results indicate that optimization approaches are suitable alternatives for scheduling and track allocation at classification yards.

  • 32.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Gestrelius, Sara
    RISE, Swedish ICT, SICS.
    Dahms, Florian
    Mihalák, Matúš
    Flier, Holger
    Optimized shunting with mixed-usage tracks2013Report (Other academic)
    Abstract [en]

    We consider the planning of railway freight classification at hump yards, where the problem involves the formation of departing freight train blocks from arriving trains subject to scheduling and capacity constraints. The hump yard layout considered consists of arrival tracks of sufficient length at an arrival yard, a hump, classification tracks of non-uniform and possibly non-sufficient length at a classification yard, and departure tracks of sufficient length. To increase yard capacity, freight cars arriving early can be stored temporarily on specific mixed-usage tracks. The entire hump yard planning process is covered in this paper, and heuristics for arrival and departure track assignment, as well as hump scheduling, have been included to provide the neccessary input data. However, the central problem considered is the classification track allocation problem. This problem has previously been modeled using direct mixed integer programming models, but this approach did not yield lower bounds of sufficient quality to prove optimality. Later attempts focused on a column generation approach based on branch-and-price that could solve problem instances of industrial size. Building upon the column generation approach we introduce a direct arc-based integer programming model, where the arcs are precedence relations between blocks on the same classification track. Further, the most promising models are adapted for rolling-horizon planning. We evaluate the methods on historical data from the Hallsberg shunting yard in Sweden. The results show that the new arc-based model performs as well as the column generation approach. It returns an optimal schedule within the execution time limit for all instances but from one, and executes as fast as the column generation approach. Further, the short execution times of the column generation approach and the arc-indexed model make them suitable for rolling-horizon planning, while the direct mixed integer program proved to be too slow for this. Extended analysis of the results shows that mixing was only required if the maximum number of concurrent trains on the classification yard exceeds 29 (there are 32 available tracks), and that after this point the number of extra car roll-ins increases heavily.

  • 33.
    Bohlin, Markus
    et al.
    SICS Swedish ICT, Kista, Sweden.
    Gestrelius, Sara
    SICS Swedish ICT, Kista, Sweden.
    Fahimeh, Khoshniyat
    SICS Swedish ICT, Kista, Sweden.
    Simulation of planning strategies for track allocation at marshalling yards2013In: WIT Transactions on Modelling and Simulation, Volume 55, 2013, Ashurst, Southampton: WIT Press, 2013, Vol. 55, p. 465-475Conference paper (Refereed)
    Abstract [en]

    Planning the operational procedures in a railway marshalling yard is a complex problem. When a train arrives at a marshalling yard, it is uncoupled at an arrival yard and then its cars are rolled to a classification yard. All cars should eventually be rolled to the classification track that has been assigned to the train they're supposed to depart with. However, there is normally not enough capacity to compound all trains at once. In Sweden, cars arriving before a track has been assigned to their train can be stored on separate tracks called mixing tracks. All cars on mixing tracks will be pulled back to the arrival yard, and then rolled to the classification yard again to allow for reclassification. Today all procedures are planned by experienced dispatchers, but there are no documented strategies or guidelines for efficient manual planning. The aim of this paper is to examine operational planning strategies that could help dispatchers find a feasible marshalling schedule that minimizes unnecessary mixing. In order to achieve this goal, two different online planning strategies have been tested using deterministic and stochastic simulation. The Hallsberg marshalling yard was used as a case study, and was simulated for the time period between December 2010 and May 2011. The first tested strategy simply assigns tracks to trains on a first come-first served basis, while the second strategy uses time limits to determine when tracks should be assigned to departing trains. The online planning algorithms have been compared with an offline optimized track allocation. The results from both the deterministic and the stochastic simulation show that the optimized allocation is better than all online strategies and that the second strategy with a time limit of 32 hours is the best online method.

  • 34.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Gestrelius, Sara
    RISE, Swedish ICT, SICS.
    Khoshniyat, Fahimeh
    Evaluation of planning policies for marshalling track allocation using simulation2012Report (Other academic)
    Abstract [en]

    Planning the operational procedures in a railway marshalling yard is a complex problem. When a train arrives at a marshalling yard, it is uncoupled on an arrival yard and then its cars are rolled to a classification yard. All cars should eventually be rolled to the classification track that has been assigned to the train they’re supposed to depart with. However, there is normally not enough capacity to compound all trains at once. In Sweden, cars arriving before a track has been assigned to their train can be stored on separate tracks called mixing tracks. All cars on mixing tracks will be pulled back to the arrival yard, and then rolled to the classification yard again to allow for reclassification. Today all procedures are planned by experienced dispatchers, but there are no documented strategies or guidelines for efficient manual planning. The aim of this paper is to examine operational planning strategies that could help dispatchers find a feasible marshalling schedule that minimizes unnecessary mixing. In order to achieve this goal, two different online planning strategies have been tested using deterministic and stochastic simulation. The Hallsberg marshalling yard was used as a case study, and was simulated for the time period between December 2010 and May 2011. The first tested strategy simply assigns tracks to trains on a first come-first served basis, while the second strategy uses time limits to determine when tracks should be assigned to departing trains. The online planning algorithms have been compared with an offline optimized track allocation. The results from both the deterministic and the stochastic simulation show that the optimized allocation is better than all online strategies and that the second strategy with a time limit of 32 hours is the best online method.

  • 35.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Gestrelius, Sara
    RISE, Swedish ICT, SICS.
    Khoshniyat, Fahimeh
    Simulation of planning strategies for track allocation at marshalling yards2013Conference paper (Refereed)
  • 36.
    Bohlin, Markus
    et al.
    KTH, School of Architecture and the Built Environment (ABE).
    Hansmann, R.
    Zimmermann, U. T.
    Optimization of Railway Freight Shunting2018In: Handbook of Optimization in the Railway Industry, Springer-Verlag New York, 2018, p. 181-212Chapter in book (Refereed)
    Abstract [en]

    Railway freight shunting is the process of forming departing trains from arriving freight trains. The process is continuously performed at rail yards. The shunting procedure is complex and rail yards constitute bottlenecks in the rail freight network, often causing delays to individual shipments. One of the problems is that planning for the allocation of tracks at rail yards is difficult, given that the planner has limited resources (tracks, shunting engines, etc.) and needs to foresee the consequences of committed actions for the current inbound trains. The required schedules highly depend on the particular infrastructure of the rail yard, on the configuration of inbound and outbound trains, and on the business objectives. Thus, new optimization tools as active decision support for the dispatchers are closely tailored to the actual processes. Due to its practical relevance, a broad range of variants has been discussed and solved by the scientific community in recent years. For selected relevant variants, we describe their fruitful relation to scientific research topics such as graph coloring, sequence partitioning, and scheduling, we discuss their computational complexity and approximability, and we outline efficient optimization procedures. In particular, we consider a set of models and algorithms which are applicable in practice, and discuss their application to the shunting yards in Ludwigshafen, Germany and in Hallsberg, Sweden. We also discuss similarities and differences between the different approaches and outline the need for future research.

  • 37.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Holst, Anders
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Ekman, Jan
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Sellin, Ola
    Lindström, Björn
    Larsen, Stefan
    Statistical Anomaly Detection for Train Fleets2012Conference paper (Refereed)
  • 38.
    Bohlin, Markus
    et al.
    Mälardalen University, Department of Computer Science and Electronics.
    Hänninen, Kaj
    Mälardalen University, Department of Computer Science and Electronics.
    Mäki-Turja, Jukka
    Mälardalen University, Department of Computer Science and Electronics.
    Shared Stack Analysis in Transaction-Based Systems2007In: Work in Progress Proceedings RTSS'07, Tucson, Arizona, USA, 2007, p. 37-40Conference paper (Refereed)
    Abstract [en]

    In this paper, we present our ongoing work on shared stack analysis for hybrid (static and dynamic) scheduled fixed priority systems. We present two methods that extend our previous work to support stack analysis for the general tasks model with offsets where several transactions can share a common run-time stack. The aim of this work is to support stack analysis of a wider range of systems. 

  • 39.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Hänninen, Kaj
    Mäki-Turja, Jukka
    Shared stack analysis in transaction-based systems2007Conference paper (Refereed)
  • 40.
    Bohlin, Markus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Hänninen, Kaj
    Mälardalen University, School of Innovation, Design and Engineering.
    Mäki-Turja, Jukka
    Mälardalen University, School of Innovation, Design and Engineering.
    Carlson, Jan
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolin, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Safe Shared Stack Bounds in Systems with Offsets and Precedences2008Report (Other academic)
    Abstract [en]

    The paper presents two novel methods to bound the stack memory used in preemptive, shared stack, real-time systems. The first method is based on branch-and-bound search for possible preemption patterns, and the second one approximates the first in polynomial time. The work extends previous methods by considering a more general taskmodel, in which all tasks can share the same stack. In addition, the new methods account for precedence and offset relations. Thus, the methods give tight bounds for a large set of realistic systems. The methods have been implemented and a comprehensive evaluation, comparing our new methods against each other and against existing methods, is presented. The evaluation shows that our exact method can significantly reduce the amount of stack memory needed. In our simulations, a decrease in the order of 40% was typical, with a runtime in the order of seconds. Our polynomial approximation consequently yields about 20% higher bound than the exact method. 

  • 41.
    Bohlin, Markus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Hänninen, Kaj
    Mälardalen University, School of Innovation, Design and Engineering.
    Mäki-Turja, Jukka
    Mälardalen University, School of Innovation, Design and Engineering.
    Carlson, Jan
    Mälardalen University, School of Innovation, Design and Engineering.
    Sjödin, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Bounding Shared-Stack Usage in Systems with Offsets and Precedences2008In: ECRTS 2008: PROCEEDINGS OF THE 20TH EUROMICRO CONFERENCE ON REAL-TIME SYSTEMS, 2008, p. 276-285Conference paper (Refereed)
    Abstract [en]

    The paper presents two novel methods to bound the stack memory used in preemptive, shared stack, real-time systems. The first method is based on branch-and-bound search for possible preemption patterns, and the second one approximates the first in polynomial time. The work extends previous methods by considering a more general task-model, in which all tasks can share the same stack. In addition, the new methods account for precedence and offset relations. Thus, the methods give tight bounds for a large set of realistic systems. The methods have been implemented and a comprehensive evaluation, comparing our new methods against each other and against existing methods, is presented. The evaluation shows that our exact method can significantly reduce the amount of stack memory needed.

  • 42.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Hänninen, Kaj
    Mäki-Turja, Jukka
    Nolin, Mikael
    Bounding shared-stack usage in systems with offsets and precedences2008Conference paper (Refereed)
    Abstract [en]

    The paper presents two novel methods to bound the stack memory used in preemptive shared stack.

  • 43.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Kocjan, Waldemar
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Designing Global Scheduling Constraints for Local Search: A Generic Approach2002Report (Other academic)
    Abstract [en]

    In this work we present a novel method to automate the computation of global constraints cost for local search. The method is based on the representation of a global constraints as graph properties on a binary constraint network. This formulation simplifies the implementation of global constraints in local search, and provides a cost that can be readily compared to one obtained for subproblems using binary constraints exclusively. The cost obtained can be efficiently updated during the search using incremental methods. The representation of a global constraint as outlined above can also be used for generation of suitable neighborhoods for the constraint. This is done using simple repair functions applied on the elementary constraints in the global constraint graph. We show the usability of our approach by presenting formulations of global constraints in non-overlapping and cumulative scheduling.

  • 44.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Aronsson, Martin
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Forsgren, Malin
    RISE - Research Institutes of Sweden, ICT, SICS.
    Ansatser för flexibel planering och schemaläggning av tågtidtabeller2006Report (Other academic)
    Abstract [sv]

    Rapporten beskriver möjliga ansatser för att lösa det abstraherade tidtabellproblemet som bl.a. diskuteras i rapporten "Leveranstågplan: Specifikation och åtagande" (DDTP Arbetsdokument SICS-DDTP-002). Till grund för de olika ansatserna ligger en modell med avgångstider och hålltider (dvs. väntetider och i viss mån traverseringstider) som tillåts variera inom vissa tidsintervall. Huvudidén är att arbeta med förenklade kapacitetsvillkor på bana och bangård, för att på ett effektivt sätt kunna beräkna tidtabeller på en nivå som tillåter anpassning av tidtabellen till det gällande transportbehovet och den rådande trafiksituationen.

  • 45.
    Bohlin, markus
    et al.
    SICS.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Kreuger, Per
    SICS, Sweden.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Best-Effort Simulation-Based Timing Analysis using Hill-Climbing with Random Restarts2009In: In Proc. of RTCSA, Aug. 2009., 2009Conference paper (Refereed)
  • 46.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Lu, Yue
    Kraft, Johan
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Nolte, Thomas
    Best-Effort Simulation-Based Timing Analysis using Hill-Climbing with Random Restarts2009In: Proceedings of the 15th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, IEEE Computer Society , 2009, 6Conference paper (Refereed)
  • 47.
    Bohlin, Markus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Kreuger, Per
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Simulation-Based Timing Analysis of Complex Real-Time Systems2009In: 2009 15TH IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND REAL-TIME COMPUTING SYSTEMS AND APPLICATIONS, PROCEEDINGS, 2009, p. 321-328Conference paper (Refereed)
    Abstract [en]

    This paper presents an efficient best-effort approach for simulation-based timing analysis of complex real- time systems. The method can handle in principle any software design that can be simulated, and is based on controlling simulation input using a simple yet novel hill- climbing algorithm. Unlike previous approaches, the new algorithm directly manipulates simulation parameters such as execution times, arrival jitter and input. An evaluation is presented using six different simulation models, and two other simulation methods as reference: Monte Carlo simulation and MABERA. The new method proposed in this paper was 4-11% more accurate while at the same time 42 times faster, on average, than the reference methods.

  • 48.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Pearson, JustinÅgren, Magnus
    Proceedings of LSCS'04, the 1st International Workshop on Local Search Techniques in Constraint Satisfaction2004Conference proceedings (editor) (Refereed)
  • 49.
    Bohlin, Markus
    et al.
    Swedish Institute of Computer Science, Sweden.
    Wärja, Mathias
    Siemens Industrial Turbomachinery AB, Sweden.
    Maintenance optimization with duration-dependent costs2015In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 224, no 1, p. 1-23Article in journal (Refereed)
    Abstract [en]

    High levels of availability and reliability are essential in many industries where production is subject to high costs due to downtime. Examples include the mechanical drive in natural gas pipelines and power generation on oil platforms, where gas turbines are commonly used as a power source. To mitigate the effects of service outages and increase overall reliability, it is also possible to use one or more redundant units serving as cold standby backup units. In this paper, we consider preventive maintenance optimization for parallel k-out-of-n multi-unit systems, where production at a reduced level is possible when some of the units are still operational. In such systems, there are both positive and negative effects of grouping activities together. The positive effects come from parallel execution of maintenance activities and shared setup costs, while the negative effects come from the limited number of units which can be maintained at the same time. To show the possible economic effects, we evaluate the approach on models of two production environments under a no-fault assumption. We conclude that savings were substantial in our experiments on preventive maintenance, compared to a traditional preventive maintenance plan. For single-unit systems, costs were on average 39 % lower when using optimization. For multi-unit systems, average savings were 19 %. We also used the optimization models to evaluate the effects of re-planning at breakdown and effects due to modeling of inclusion relations. Breakdown re-planning saved between 0 and 11 % of the maintenance costs, depending on which component failed, while inclusion relation modeling resulted in an 7 % average cost reduction.

  • 50.
    Bohlin, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Wärja, Mathias
    Maintenance Optimization with Duration-Dependent Costs2012In: Annals of Operations ResearchArticle in journal (Refereed)
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