Traveling Salesman Problems With Replenishment Arcs and Improved Ant Colony Algorithms

被引：1
|
作者：
Zeng, Xiaoxu [1 ,2 ]
Song, Qi [3 ]
Yao, Song [1 ]
Tian, Zhiqiang [3 ]
Liu, Qinglei [2 ]
机构：
[1] Cent South Univ, Sch Traff & Transportat Engn, Changsha 410083, Peoples R China
[2] Tianjin Rail Transit Operat Grp Co Ltd, Tianjin 300392, Peoples R China
[3] Lanzhou Jiaotong Univ, Sch Traff & Transportat, Lanzhou 730070, Peoples R China
来源：
IEEE ACCESS | 2021年 / 9卷
基金：
中国国家自然科学基金;
关键词：
Urban areas; Optimization; Heuristic algorithms; Transportation industry; Task analysis; Standards; Personnel; Cumulative travel constraints; dynamic replenishment arc; improved ant colony algorithm; traveling salesman problem;
D O I：
10.1109/ACCESS.2021.3093295
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The traveling salesman problem (TSP), can be used as a typical combinatorial optimization problem, to describe a wide variety of practical engineering optimization problems in various fields. In this study, the problem of personnel and equipment utilization in the transportation industry was abstracted, a more general class of TSPs with replenishment arcs was proposed, an optimization model to minimize the total travel time was established, the ant colony optimization algorithm to solve the standard TSP was improved, and an improved ant colony algorithm based on dynamic heuristic information was designed. Simulation experiments showed that the algorithm can account for the cumulative mileage constraint and search for the shortest path, effectively solving the TSP with replenishment arcs.
引用
收藏
页码：101042 / 101051
页数：10
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