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.
Highlights
Today, the demand of the goods distribution is increasingly personalized and diversified, many small and medium-sized enterprises are becoming increasingly aware that they cannot cope with the huge distribution demand on the basis of their finite capacity, so have begun to take a collectivized approach to quickly adapt to the market change and improve their competitiveness [1]–[3]
An optimization model for partner selection is established in which the supply-demand matching degree and the total operation cost are designed as optimization objectives
The results show that the partner selection model of Joint distribution alliance (JDA) is feasible
Summary
The demand of the goods distribution is increasingly personalized and diversified, many small and medium-sized enterprises are becoming increasingly aware that they cannot cope with the huge distribution demand on the basis of their finite capacity, so have begun to take a collectivized approach to quickly adapt to the market change and improve their competitiveness [1]–[3]. Under the condition that the JD task can be split, the requirements of a subtask are regarded as ‘‘demand’’ and the enterprise capabilities are regarded as ‘‘supply’’, a new VOLUME 7, 2019 analysis method and solution for the JDA partner selection are developed from the perspective of supply and demand matching. The calculation method of the subtask-oriented supply-demand matching degree considering the penalty function is proposed. An optimization model of JDA partner selection is designed with the objectives of the supply-demand matching degree and the total operation cost, on the basis of the subtask assignment, the subtask precedence relationships, the subtask time windows and the due date as constraints.
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