Metaheuristic algorithm for solving the multi-objective vehicle routing problem with time window and drones

被引:37
|
作者
Han, Yun-qi [1 ]
Li, Jun-qing [1 ,2 ]
Liu, Zhengmin [3 ]
Liu, Chuang [2 ]
Tian, Jie [1 ]
机构
[1] Shandong Normal Univ, Sch Informat & Engn, Jinan 250014, Shandong, Peoples R China
[2] Liaocheng Univ, Sch Comp Sci, Liaocheng, Shandong, Peoples R China
[3] Shandong Univ Finance & Econ, Sch Management Sci & Engn, Jinan, Peoples R China
来源
基金
美国国家科学基金会;
关键词
Vehicle routing problem; artificial bee colony; time window; drone transportation; multi-objective; FLEXIBLE JOB-SHOP; TRAVELING SALESMAN PROBLEM; SCHEDULING PROBLEMS; DELIVERY PROBLEM; OPTIMIZATION; PICKUP; MODEL;
D O I
10.1177/1729881420920031
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In some special rescue scenarios, the needed goods should be transported by drones because of the landform. Therefore, in this study, we investigate a multi-objective vehicle routing problem with time window and drone transportation constraints. The vehicles are used to transport the goods and drones to customer locations, while the drones are used to transport goods vertically and timely to the customer. Three types of objectives are considered simultaneously, including minimization of the total energy consumption of the trucks, total energy consumption of the drones, and the total number of trucks. An improved artificial bee colony algorithm is designed to solve the problem. In the proposed algorithm, each solution is represented by a two-dimensional vector, and the initialization method based on the Push-Forward Insertion Heuristic is embedded. To enhance the exploitation abilities, an improved employed heuristic is developed to perform detailed local search. Meanwhile, a novel scout bee strategy is presented to improve the global search abilities of the proposed algorithm. Several instances extended from the Solomon instances are used to test the performance of the proposed improved artificial bee colony algorithm. Experimental comparisons with the other efficient algorithms in the literature verify the competitive performance of the proposed algorithm.
引用
收藏
页数:14
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