Original scientific paper

https://doi.org/10.17559/TV-20230812000875

Optimization of Multi-temperature Joint Distribution Paths for Convenience Store Chains

Yuanyuan Zhang ; College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China *
Yicheng Chen ; College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Peidong Yu ; College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Xianglong Li ; College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Yuhang Wang ; School of Public Administration & Law, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Junjing Zhang ; College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Jie Pang ; College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China

* Corresponding author.

Abstract

Purpose - Convenience stores are the main driving force of the small retail format in China. In order to meet customer demands, maintain product quality, reduce waste, and stay competitive in the fast-paced retail environment, convenience stores conduct daily food deliveries, with transportation costs accounting for the largest share of logistics expenses. Consequently, the daily operation costs of chain convenience stores increase. Therefore, the aim of this paper is to optimize the distribution paths of chain convenience stores with multiple distribution centers in order to reduce operational costs, reduce carbon dioxide emissions, etc. Design/methodology/approach - A mathematical model of the multi-temperature joint distribution problem with multiple distribution centers was constructed to minimize the total cost. In the model, six kinds of costs were considered. In addition, a two-stage algorithm was designed. The K-means algorithm was used to cluster match the demand points with the distribution centers, and the genetic algorithm was used to solve the routing problem of each distribution center. Subsequently, the costs of the multi-temperature joint distribution and multi-vehicle distribution were compared. Findings - The results showed that the optimization rate of total cost was 26.35%, the optimization rate of other costs was greater than 45%. Note that through case solving, the K-means algorithm was used to convert the single problem of multiple distribution centers into multiple problems of one distribution center. The multi-temperature joint distribution pattern was applied to the food distribution of chain convenience stores so that they could improve the delivery time and reduce the number of vehicles, carbon dioxide emissions, and total cost. Originality/value - Previous research on multi-temperature joint deliveries has predominantly focused on distribution from a single distribution center, overlooking the study of multi-distribution center scenarios. This article addresses this gap and explores the feasibility of applying a multi-temperature joint delivery service model to food distribution for chain convenience stores with multiple distribution centers.

Keywords

multiple distribution centers; multi-temperature joint distribution; path optimization of chain convenience stores

Hrčak ID:

320412

URI

https://hrcak.srce.hr/320412

Publication date:

31.8.2024.

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