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.
