Decomposition heuristic to minimize total cost in a multi-level supply chain network

In this paper, the distribution planning model for the multi-level supply chain network is studied. Products which are manufactured at factory are delivered to customers through warehouses and distribution centers for the given customer demands. The objective function of suggested model is to minimize logistic costs such as replenishment cost, inventory holding cost and transportation cost. A mixed integer programming formulation and heuristics for practical use are suggested. Heuristics are composed of two steps: decomposition and post improving process. In the decomposition heuristics, the problems are solved optimally only considering the transportation route first by the minimum cost flow problem, and the replenishment plan is generated by applying the cost-saving heuristic which was originally suggested in the manufacturing assembly line operation, and integrating with the transportation plan. Another heuristic, in which the original model is segmented due to the time periods, and run on a rolling horizon based method, is suggested. With the post-improving process using tabu search method, the performances are evaluated, and it was shown that solutions can be computed within a reasonable computation time by the gap of about 10% in average from the lower bound of the optimal solutions.