An integrative cooperative search framework for multi-decision-attribute combinatorial optimization: Application to the MDPVRP

Nadia Lahrichi, Teodor Gabriel Crainic, Michel Gendreau, Walter Rei, Gloria Cerasela Crişan and Thibaut Vidal

European Journal of Operational Research, 2015, vol. 246, issue 2, 400-412

Abstract: We introduce the integrative cooperative search method (ICS), a multi-thread cooperative search method for multi-attribute combinatorial optimization problems. ICS musters the combined capabilities of a number of independent exact or meta-heuristic solution methods. A number of these methods work on sub-problems defined by suitably selected subsets of decision-set attributes of the problem, while others combine the resulting partial solutions into complete ones and, eventually, improve them. All these methods cooperate through an adaptive search-guidance mechanism, using the central-memory cooperative search paradigm. Extensive numerical experiments explore the behavior of ICS and its interest through an application to the multi-depot, periodic vehicle routing problem, for which ICS improves the results of the current state-of-the-art methods.

Keywords: Multi-attribute combinatorial optimization; Integrative cooperative search; Meta-heuristics; Decision-set decomposition; Multi-depot periodic vehicle routing (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:246:y:2015:i:2:p:400-412

DOI: 10.1016/j.ejor.2015.05.007

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