Research article

Optimization of the supply chain network planning problem using an improved genetic algorithm

¹ Department of Railway Engineering, Zhengzhou Railway Vocational and Technical College, Zhengzhou, Henan 450000, China
² Innovation and Entrepreneurship Institute, Zhengzhou Railway Vocational and Technical College, Zhengzhou, Henan 450000, China

^* e-mail: 11138@zzrvtc.edu.cn

Received: 19 July 2023
Accepted: 1 September 2023

Abstract

The planning problem of supply chain network is highly related to logistics cost and product quality. In this paper, for the optimization of supply chain network planning problem, an agricultural product supply chain network under the direct docking model between farmers and supermarkets was taken as an example to establish an agricultural product supply chain network planning model with the lowest cost as the objective. Then, an improved genetic algorithm (GA) was designed to solve the model. The analysis of the arithmetic example showed that compared with the traditional GA, the total cost obtained by the improved GA was lower, at 39,004.48 $, which was 6.5% less than that of the traditional GA; the solution result of the improved GA was also superior to that of other heuristic algorithms, such as particle swarm optimization and ant colony optimization. The experimental results demonstrate the optimization effectiveness of the improved GA for the supply chain network planning problem, and it can be applied in practice.