An integrative cooperative search framework for multi-decision-attribute combinatorial optimization: Application to the MDPVRP. Lahrichi, N., Crainic, T., Gendreau, M., Rei, W., Crisan, G., & Vidal, T. European Journal of Operational Research, 246(2):400–412, 2015.
An integrative cooperative search framework for multi-decision-attribute combinatorial optimization: Application to the MDPVRP [pdf]Paper  doi  abstract   bibtex   
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.

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