A hybrid differential evolution algorithm for a location-inventory problem in a closed-loop supply chain with product recovery

Autor: Hao Guo, Gang Liu, Ying Zhang, Chunnan Zhang, Chuanhui Xiong, Wenli Li
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Complex & Intelligent Systems, Vol 9, Iss 4, Pp 4123-4145 (2022)
Druh dokumentu: article
ISSN: 2199-4536
2198-6053
DOI: 10.1007/s40747-022-00930-3
Popis: Abstract Product recovery is an important business because of its great economic, social, and environmental benefits in practice. In this paper, a location-inventory problem (LIP) in a closed-loop supply chain (CLSC) is investigated to optimize facility location and inventory control decisions by considering product recovery. The objective is to optimize facility location and inventory control decisions to minimize the total cost of business operations in a closed-loop supply chain system. We formulate this problem as a mixed-integer nonlinear programming model and design a modified hybrid differential evolution algorithm (MHDE) to solve it efficiently. Finally, numerical results are presented to validate the performance of the new algorithm. The results show that MHDE is more efficient and effective than Lingo and other algorithms for the research problem under study. Managerial insights are also derived for business managers to improve their supply chain performance.
Databáze: Directory of Open Access Journals
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