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Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-1377-8949
Dalarna University, School of Technology and Business Studies, Computer Engineering.
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2014 (English)In: Journal of Intelligent Learning Systems and Applications, ISSN 2150-8402, E-ISSN 2150-8410, Vol. 6, no 2, 125-139 p.Article in journal (Refereed) Published
Abstract [en]

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Place, publisher, year, edition, pages
2014. Vol. 6, no 2, 125-139 p.
Keyword [en]
Simulation, Genetic Algorithm, Simulated Annealing, Planning and Arrangement, Decision Making, Storage Bins, Log Stackers and Sawmill Yard
National Category
Computer and Information Science
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-19459DOI: 10.4236/jilsa.2014.62010OAI: oai:DiVA.org:du-19459DiVA: diva2:853803
Available from: 2015-09-15 Created: 2015-09-15 Last updated: 2017-12-04Bibliographically approved

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