Supplier Selection and Multi-period Demand Allocation in a Humanitarian Supply Chain

This paper presents a hybrid algorithm for multi-period demand allocation in humanitarian supply chain. This hybrid algorithm prioritizes the suppliers and then allocates the multi-period demand among the suppliers. The objective here is to maximize the total value of procurement taking into consideration multi-period demand condition, budget constraint, delivery lead time, and multi-period supplier capacity. Since the problem is multi-criteria decision making, we solve this problem by integrating the supplier rating with mixed linear integer programming method. The customer demand is allocated by using a hybrid algorithm based on the technique for order preference by similarity to ideal solution (TOPSIS) and the mixed linear integer programming (MILP) approaches. The effectiveness of the proposed algorithm is validated with computational results. Drawing to a case, under constrained scenario, suppliers S1 and S2 are identified as the best suppliers by using the hybrid algorithm for multi-period demand allocation among suppliers. The maximum units are allocated to these suppliers, and this allocation maximizes the value of the procurement. On the contrary, under no constrained scenario, the individual approach (i.e., TOPSIS) assigns the lowest rating to the supplier S1. These observations prove that the hybrid algorithm improves the efficacy of the individual approaches.