Green Logistics Location-Routing Optimization Solution Based on Improved GA A1gorithm considering Low-Carbon and Environmental Protection
Anqing Zhu,
Youyun Wen and
Melike Kaplan
Journal of Mathematics, 2021, vol. 2021, 1-16
Abstract:
This paper proposes a green logistics location-routing optimization problem based on improved genetic algorithm (GA) from the perspective of low-carbon and environmental protection. First, considering the cost factor, time window, deterioration rate of agricultural products, inventory and distribution capacity, carbon trading mechanism, and other factors, and with the total cost minimization as the optimization goal, a low-carbon and environmental protection logistics location-routing optimization model is constructed. Then, the adaptive operator and cataclysm operator are introduced to improve the GA algorithm, which can adjust crossover and mutation probability according to the needs, reducing the influence of parameters and running time. Furthermore, the improved GA algorithm is used to solve the location-routing optimization problem in green logistics, so as to obtain a low-carbon, economical, and efficient distribution path. Finally, perform experimental analysis of the proposed method using the relevant data of U company. The results show that the total distribution cost is 6771.3 yuan, which meets the design requirements of economy and environmental protection.
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:6101194
DOI: 10.1155/2021/6101194
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