An Optimization Model of Partner Selection of Joint Distribution Alliance Considering the Supply and Demand Matching Degree

Abstract

The partner selection problem (PSP) of Joint Distribution (JD) is investigated when the joint distribution task can be split into multiple subtasks. In order to select the optimal partner to complete the joint distribution task, a new analysis method and solution for the partner selection problem of joint distribution alliance (JDA) are provided from the perspective of supply and demand matching. First, the definition of supply and demand matching between the subtasks and the candidate enterprises is introduced, and a mathematical description of the subtask-oriented supply-demand matching degree is proposed. Second, an optimization model for joint distribution partner selection is established, which aims at maximizing the supply-demand matching degree and minimizing the total operation cost. Third, as the problem is NP-hard, a hybrid algorithm combining a particle swarm optimization (PSO) algorithm and a genetic algorithm (GA) is proposed to find the Pareto-optimal solutions. Finally, the feasibility of the proposed model is demonstrated in a numerical experiment and the hybrid algorithm is compared with the standard PSO algorithm and GA.