An efficient bi-objective optimization approach for the optimal design of omnichannel supply chain distribution networks with sustainability

Abstract

This article studies a bi-objective omnichannel supply chain network design (SCND) problem, while simultaneously minimizing the overall supply chain (SC) cost and associated environmental emissions. A novel bi-objective mixed integer linear programming model is formulated, then an efficient optimization approach is proposed for the problem. Experimental studies on a case study and 210 random testing instances were conducted to evaluate the performance of the proposed model and approach. For the case study, 10 Pareto-optimal solutions were obtained within 1.9 s. For the random testing instances, the average number of Pareto-optimal solutions and computational time were 10.19 and 18.85 s, respectively. The overall results show that the proposed method is efficient and outperforms the adapted non-dominated sorting genetic algorithm II on test instances. Computational results indicate that this approach could assist decision makers in making good decisions, with considerable SC cost saving and carbon emission reductions in different situations.

KEYWORDS:

• Supply chain network design
• omnichannel
• carbon emission
• bi-objective optimization
• MILP model

Acknowledgements

The authors thank the anonymous reviewers and editors for their valuable suggestions, which have greatly improved the technical accuracy and presentation of this article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Weidong Lei, upon reasonable request.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61902039], the Natural Science Basic Research Plan in Shaanxi Province of China [grant number 2024JC-YBQN-0749], the Humanity and Social Science Foundation of Ministry of Education of China [grant number 23YJAZH27, 23XJCZH016] and the Innovation Capability Support Plan project of Shaanxi Province [grant number 2024ZC-YBXM-128].