Learning Mechanisms and Local Search Heuristics for the Fixed Charge Capacitated Multicommodity Network Design
نویسندگان
چکیده
In this paper, we propose a method based on learning mechanisms to address the fixed charge capacitated multicommodity network design problem. Learning mechanisms are applied on each solution to extract meaningful fragments to build a pattern solution. Cycle-based neighborhoods are used both to generate solutions and to move along a path leading to the pattern solution by a tabu-like local search procedure. Within this concept, the method integrates important mechanisms such as intensification and diversification. Experimental results show that the proposed algorithm is effective for large structured instances with several commodities.
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