The CAT metaheuristic for the solution of multi-period activity-based supply chain network design problems
This paper proposes an agent-based metaheuristic to solve large-scale multi-period supply chain network design problems. The generic design model formulated covers the entire supply chain, from vendor selection, to production–distribution sites configuration, transportation options and marketing pol...
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Published in | International journal of production economics Vol. 139; no. 2; pp. 664 - 677 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.10.2012
Elsevier Sequoia S.A |
Subjects | |
Online Access | Get full text |
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Summary: | This paper proposes an agent-based metaheuristic to solve large-scale multi-period supply chain network design problems. The generic design model formulated covers the entire supply chain, from vendor selection, to production–distribution sites configuration, transportation options and marketing policy choices. The model is based on the mapping of a conceptual supply chain activity graph on potential network locations. To solve this complex design problem, we propose Collaborative Agent Team (CAT), an efficient hybrid metaheuristic based on the concept of asynchronous agent teams (A-Teams). Computational results are presented and discussed for large-scale supply chain networks, and the results obtained with CAT are compared to those obtained with the latest version of CPLEX. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0925-5273 1873-7579 |
DOI: | 10.1016/j.ijpe.2012.06.016 |