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A multi-center joint distribution optimization model considering carbon emissions and customer satisfaction.
Ren, Xiangyang; Jiang, Xinxin; Ren, Liyuan; Meng, Lu.
Afiliação
  • Ren X; School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, China.
  • Jiang X; School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, China.
  • Ren L; School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, China.
  • Meng L; School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, China.
Math Biosci Eng ; 20(1): 683-706, 2023 Jan.
Article em En | MEDLINE | ID: mdl-36650784
Logistics enterprises are searching for a sustainable solution between the economy and the environment under the concept of green logistics development. Given that, this study integrates carbon emission as one of the costs into the vehicle routing problem with time window (VRPTW) and establishes a multi-center joint distribution optimization model taking into account distribution cost, carbon emission, and customer satisfaction. In the study of carbon emissions, this paper selected the vehicle load rate and vehicle distance as the main indicators. An improved ant colony algorithm is designed to solve the model by introducing the elite strategy, the saving strategy, vehicle service rules, and customer selection rules. Simulation results show that compared with the traditional ant colony optimization and genetic algorithm, the improved ant colony algorithm can effectively reduce the distribution cost and carbon emission and, improve customer satisfaction.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Revista: Math Biosci Eng Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Revista: Math Biosci Eng Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: Estados Unidos