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Joint optimization decision of service provider selection and CODP positioning based on mass customization in a cloud logistics environment

Guanxiong Wang (School of Business, Anhui University, Hefei, China)
Xiaojian Hu (School of Management, Hefei University of Technology, Hefei, China)
Ting Wang (Department of Basic, Anhui Sanlian University, Hefei, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 27 February 2023

Issue publication date: 13 March 2024

215

Abstract

Purpose

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

Design/methodology/approach

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

Findings

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

Originality/value

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Keywords

Acknowledgements

This research is supported by the Humanities and Social Sciences Project of Anhui Provincial Department of Education (SK2020A0037), Anhui province Natural Science Foundation (2108085QG294) and the National Nature Science Foundation of China (Nos.72171067). The authors also thank the reviewers and editors.

Citation

Wang, G., Hu, X. and Wang, T. (2024), "Joint optimization decision of service provider selection and CODP positioning based on mass customization in a cloud logistics environment", Kybernetes, Vol. 53 No. 4, pp. 1411-1433. https://doi.org/10.1108/K-04-2022-0642

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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