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  • 1.
    Jianqiang, Cheng
    et al.
    Univ. Paris Sud, France.
    Kosuch, Stefanie
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Lisser, Abdel
    Univ. Paris Sud, France.
    Stochastic Shortest Path Problem with Uncertain Delays2012In: Proceedings of the 1st International Conference on Operations Research and Enterprise Systems (ICORES-2012 / [ed] Carlos J. Luz, Fernando Valente, 2012, p. 256-264Conference paper (Other academic)
  • 2.
    Kosuch, Stefanie
    Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory. Linköping University, The Institute of Technology.
    An Ant Colony Optimization Algorithm for the Two-stage Knapsack Problem2011In: Proceedings of the 10th Biennial International Conference on Artificial Evolution / [ed] Jin-Kao Hao, Pierrick Legrand, Pierre Collet, Nicolas Monmarché, Evelyne Lutton, Marc Schoenauer, 2011, p. 166-179Conference paper (Refereed)
    Abstract [en]

    We propose an Ant Colony Optimization algorithm for the Two-Stage Knapsack problem with discretely distributed weights and capacity. To the best of our knowledge this is the first attempt to solve a Two-Stage Knapsack problem using a metaheuristic. Two heuristic utility measures are proposed and compared. Moreover, we introduce the novel idea of non-utility measures in order to obtain a criterion for the construction termination. We argue why for the proposed measures it is more efficient to place pheromone on arcs instead of vertices or edges of the complete search graph. Numerical tests show that our algorithmis able to produce, in much shorter computing time, solutions of similar quality than CPLEX after 2h. Moreover, with increasing number of scenarios the percentage of runs where our algorithm is able to produce better solutions than CPLEX (after 2h) increases.

  • 3.
    Kosuch, Stefanie
    Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory. Linköping University, The Institute of Technology.
    Approximability of the Two-stage Knapsack Problem with Discretely Distributed Weights2011In: Proceedings of the 10th Cologne-Twente Workshop on Graphs and Combinatorial Optimization / [ed] Ludovica Adacher, Marta Flamini, Gianmaria Leo, Gaia Nicosia, Andrea Pacifici, Veronica Piccialli, 2011, p. 180-183Conference paper (Refereed)
  • 4.
    Kosuch, Stefanie
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Approximability of the two-stage stochastic knapsack problem with discretely distributed weights2014In: Discrete Applied Mathematics, ISSN 0166-218X, E-ISSN 1872-6771, Vol. 165, p. 192-204Article in journal (Refereed)
    Abstract [en]

    In this paper the two-stage knapsack problem with random weights is studied under the aspect of approximability. We assume finite probability distributions for the weights and show that, unless P = NP, the so obtained problem cannot be approximated in polynomial time within a better ratio than K-1/2 (where K is the number of second-stage scenarios). We further study the special cases where in the second stage items can only be added or only be removed, but not both. Positive approximation results are given for three particular cases, namely linearly dependent first- and second-stage rewards, the polynomial scenario model and the case where the number of scenarios is assumed to be a constant. To the best of our knowledge, this is the first study of a two-stage knapsack problem under the aspect of approximability and the first time a non-approximability result has been proven for a stochastic knapsack problem of any kind.

  • 5.
    Kosuch, Stefanie
    Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory. Linköping University, The Institute of Technology.
    Towards an Ant Colony Optimization Algorithm for the Two-stage Knapsack Problem2011In: Proceedings of the 7th ALIO/EURO Workshop on Applied Combinatorial Optimization / [ed] Ana Viana, A. Miguel Gomes, Joao Pedro Pedroso, Maria Teresa Costa, 2011, p. 27-27Conference paper (Refereed)
    Abstract [en]

    We propose an Ant-Colony-Optimization algorithm for the Two-Stage Knapsack problem (TSKP) with discretely distributed weights. Three heuristic utility measures are proposed and compared. We argue why for the proposed measures it is more efficient to place pheromone on arcs instead of vertices or edges of the complete search graph. Numerical tests show that the algorithm is able to find near optimal or even optimal solutions after a relatively small number of generated solutions.

  • 6.
    Tanasa, Bogdan
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Bordoloi, Unmesh
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Kosuch, Stefanie
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Eles, Petru Ion
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Peng, Zebo
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Schedulability Analysis for the Dynamic Segment of FlexRay: A Generalization to Slot Multiplexing2012Conference paper (Refereed)
    Abstract [en]

    FlexRay, developed by a consortium of over hundred automotive companies, is a real-time communication protocol for automotive networks. In this paper, we propose a new approach for timing analysis of the event-triggered component of FlexRay, known as the dynamic segment. Our technique accounts for the fact that the FlexRay standard allows slot multiplexing, i.e., the same priority can be assigned to more than one message. Existing techniques have either ignored slot multiplexing in their analysis or made simplifying assumptions that severely limit achieving high bandwidth utilization. Moreover, we show that our technique returns less pessimistic results compared to previously known techniques even in the case where slot multiplexing is ignored.

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