Learning Mechanisms and Local Search Heuristics for the Fixed Charge Capacitated Multicommodity Network Design
In this paper, the authors 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.