Collaborative Logistics Resource Selection Mode based on Genetic Algorithm

Abstract

Collaborative logistics is a kind of supply chain management, involving cooperation between companies to meet customer needs. This is a complex process that requires coordination among all parties. It can be divided into three main stages: planning, implementation and monitoring. The purpose of this study is to determine the best mode of resource selection in collaborative logistics using genetic algorithms. The first stage of collaborative logistics is planning, including determining customer needs, defining inventory levels, and determining transportation routes. This is a complex process because it involves many different types of resources and products. In this paper, we will discuss how to use genetic algorithms to improve collaborative logistics. When improving the collaborative logistics process, the first thing to consider is to determine all necessary resources and products required for such supply chain management. This will help eliminate unnecessary costs, because only those items that are really needed will be purchased from suppliers. This paper analyzes the framework of collaborative logistics mechanism, uses analytic hierarchy process (AHP) to preliminarily screen logistics resources to obtain the candidate resource pool required by the collaborative system, and proposes an effective resource selection process using the improved contract network protocol method based on the collaborative logistics network model. The negotiation process determines the basic rates for transportation, warehousing, and other items in the collaborative logistics system, and achieves the aggregation and collaboration of logistics tasks through solving the collaborative logistics network model. Finally, the fuzzy comprehensive evaluation method is used to calculate the allocation proportion of additional profits in the collaborative system.