Minimizing the carbon emission for the open location-routing problem and algorithm

被引：0
|
作者：
Jiang H. [1 ,2 ]
Zhao Y. [1 ]
Zhang J. [1 ]
Leng L. [1 ]
机构：
[1] The MOE Key Lab of Special Purpose Equipment and Advanced Manufacturing Technology, Zhejiang University of Technology, Hangzhou
[2] College of Modern Science and Technology, China Jiliang University, Hangzhou
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2020年 / 40卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Carbon emission; Open location-routing; Quantum-inspired evolutionary algorithm; Routing problem;
D O I：
10.12011/1000-6788-2017-1375-13
中图分类号：
学科分类号：
摘要：
It is important to study the carbon emissions of location-routing problems for reducing the carbon emission of logistics. This paper establishes an open location-routing problem model (OLRP), the goal of OLRP is to minimize the carbon emission, considering of facility construction carbon emission and distribution carbon emission. We propose a quantum-inspired evolutionary algorithm (QEA) for solving the model. The algorithm adopts the strategy of determining the vehicles and their paths first, and then selecting the distribution center. Two routing local searches and two distribution local searches are used to improve the solution. Three important parameters (Δθ_itermax_Popsize) are determined by considering the carbon emission and CPU in Prins problem. The algorithm is tested on the benchmark of Barreto_Prins and Tuzun problems, the results show that the low carbon emission target of OLRP will increase the cost. The quantum-inspired evolutionary algorithm can obtain better average results than LB_CPLEX and SA in the Barreto problem, similar results to CPLEX in the Prins problem, and better than CPLEX in most Tuzun problem, which mean that QEA is an effective algorithm to the problem of OLRP. © 2020, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码：182 / 194
页数：12
相关论文
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