Carbon reduction in the location routing problem with heterogeneous fleet, simultaneous pickup-delivery and time windows

被引:15
作者
Wang, Xuping [1 ,2 ]
Li, Xinyu [1 ]
机构
[1] Dalian Univ Technol, Inst Syst Engn, 2 Linggong Rd, Dalian 116023, Peoples R China
[2] Dalian Univ Technol, Sch Business, 2 Dagong Rd, Panjin 124221, Peoples R China
来源
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS | 2017年 / 112卷
基金
中国国家自然科学基金;
关键词
location routing problem; temporal-spatial distance; VNS; two-phase heuristic algorithm; ALGORITHM;
D O I
10.1016/j.procs.2017.08.147
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Along with the concerns about global climate change, more and more researchers pay attention to the low carbon logistics. Since the logistics industry is an important source of carbon emissions, it is becoming more and more important to reduce carbon emissions in logistics operation. In this paper, we study a low carbon for location routing problem with heterogeneous fleet, simultaneous pickup-delivery and time windows and design a two-phased hybrid heuristic algorithm to solve the problem. Firstly, we introduce the concept of temporal-spatial distance and use genetic algorithm to cluster the customer points to construct the initial path. Then, we use variable neighborhood search algorithm for local search. By incorporating the idea of simulated annealing algorithm into the framework of variable neighborhood algorithm, the global optimization ability of the algorithm is improved. At the same time, the vehicle adjustment strategy is added in the optimization process. The computational experiments are implemented to investigate the performance of the proposed heuristic algorithm. Computational results show that the initial solution considering temporal-spatial distance has obvious advantages in the efficiency of the algorithm and the quality of the solution. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:1131 / 1140
页数:10
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