Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

被引:72
作者
Zhao, Banglei [1 ]
Gui, Haixia [1 ]
Li, Huizong [2 ]
Xue, Jing [1 ]
机构
[1] Anhui Univ Sci & Technol, Sch Econ & Management, Huainan 232001, Peoples R China
[2] Nanyang Normal Univ, Sch Comp & Informat Technol, Nanyang 473061, Peoples R China
基金
中国国家自然科学基金;
关键词
Logistics; Carbon dioxide; Optimization; Customer satisfaction; Heuristic algorithms; Vehicle routing; Temperature distribution; Cold chain logistics; path optimization; multi-objective optimization; carbon constraints; customer satisfaction; VEHICLE-ROUTING PROBLEM; PARTICLE SWARM OPTIMIZATION; TABU SEARCH ALGORITHM; SUPPLY CHAIN; TIME-WINDOWS; SYSTEM; FRUIT; MANAGEMENT; DESIGN; MODEL;
D O I
10.1109/ACCESS.2020.3013951
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to improve the performance and change the current situation of the cost minimization model widely used in the cold chain logistics distribution process, a multi-objective optimization model based on cost, carbon emissions and customer satisfaction is proposed. Considering the characteristic of this proposed optimization model, we design an improved ant colony algorithm with a multi-objective heuristic function to solve it, termed as ACOMO. Experimental results show that the proposed ACOMO can effectively solve the vehicle routing problem of the multi-objective optimization model, and outperforms the classic ant colony algorithms, resulting in more Pareto optimal solutions. It offers an environmentally friendly distribution solution for the problem. Specifically, the distribution path obtained by the improved ant colony algorithm manages to achieve the above multiple goals, including reduction of distribution costs and carbon emissions, and improvement of customer satisfaction. In addition, compared with a single-target model that only provides one single distribution route to cost minimization, multi-objective optimization can provide a variety of distribution route options for logistics companies in practice. Finally, through the sensitivity analysis of temperature changes and cargo damage coefficients, the proposed system successfully provides reference for the optimization of the path of cold chain logistics enterprises, and promotes logistics enterprises to effectively arrange their work and to be more socially responsible.
引用
收藏
页码:142977 / 142995
页数:19
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