Designing an integrated multi-objective supply chain network considering volume flexibility

This paper investigates the problem of designing an integrated production-distribution system which supports strategic and tactical decision levels in supply chain management. An important aspect of this problem is consideration of volume flexibility to increase the system ability to change the level of aggregated output. The problem is formulated as a mixed integer linear programming. The objective functions are to minimize the total cost of production, location of DCs, transportation, inventory holding and backorders while maximizing flexibility level simultaneously. Since the problem under study is NP-hard, a multi-objective differential evolution (MOEM) framework is developed to solve this problem. To prove the efficiency and reliability of the proposed algorithm, the results obtained from extensive experiments are compared with the well-known multi-objective genetic algorithms in the literature, i.e. NSGA-II based on some comparison metrics. Computational experiments indicate the superiority of the MODE compared to this algorithm.