 Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain designLuis A. Moncayo-Martínez and David Z. Zhang International Journal of Production Economics, 2011, vol. 131, issue 1, 407-420 Abstract: This paper proposes a new approach to determining the Supply Chain (SC) design for a family of products comprising complex hierarchies of subassemblies and components. For a supply chain, there may be multiple suppliers that could supply the same components as well as optional manufacturing plants that could assemble the subassemblies and the products. Each of these options is differentiated by a lead-time and cost. Given all the possible options, the supply chain design problem is to select the options that minimise the total supply chain cost while keeping the total lead-times within required delivery due dates. This work proposes an algorithm based on Pareto Ant Colony Optimisation as an effective meta-heuristic method for solving multi-objective supply chain design problems. An experimental example and a number of variations of the example are used to test the algorithm and the results reported using a number of comparative metrics. Parameters affecting the performance of the algorithm are investigated. Keywords: Supply; chain; configuration; Multi-objective; optimisation; Ant; colony; Meta-heuristics (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:131:y:2011:i:1:p:407-420 Access Statistics for this article International Journal of Production Economics is currently edited by Stefan Minner More articles in International Journal of Production Economics from Elsevier |
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