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A MIP-Tabu Search Hybrid Framework for Multicommodity Capacitated Fixed-Charge Network Design

This paper addresses the capacitated multicommodity fixed-charge network design problem, a particular case of the broad class network design problems. To identify good quality solutions, we propose a matheuristic combining an exact MIP method and a Tabu search meta-heuristic. A new arc-balanced cycle procedure for generating neighboring solutions is introduced. To assess the quality of the solutions, tight lower bounds are computed using a cutting-plane procedure. During the computation process, memories characterizing attributes of solutions are compiled. These memories are then used to find good quality starting solutions in short computational times. Computational results conducted on a large set of instances with various characteristics show an efficient behavior of the proposed method. The method provides high quality feasible solutions which outperformed those obtained by state-of-the-art optimization codes within the time allowed.