A comparative study of improved GA and PSO in solving multiple traveling salesmen problem-Reference-Cited by-同舟云学术

A comparative study of improved GA and PSO in solving multiple traveling salesmen problem

Published:2018-03 Issue: Volume:64 Page:564-580
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Zhou Honglu,Song Mingli,Pedrycz Witold

Publisher

Elsevier BV

Subject

Software

Reference109 articles.

1. Aspects of the traveling salesman problem;Held;IBM J. Res. Dev.,1984

2. Cellular competitive decision algorithm for traveling salesman problem;Xiong;Enterprise Systems Conference (ES),2014

3. An improvement of fruit fly optimization algorithm for solving traveling salesman problems;Hengyu;Proc International Conference on Information and Automation (ICIA),2014

4. Comparison study of multiple traveling salesmen problem using genetic algorithm;Singh;Int. J. Comput. Sci. Netw. Secur.,2014

5. An Introduction to Genetic Algorithms;Melanie,1998

Cited by 110 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A learning-based memetic algorithm for a cooperative task allocation problem of multiple unmanned aerial vehicles in smart agriculture;Swarm and Evolutionary Computation;2024-12

2. A Branch-and-Cut algorithm for the multiple Steiner TSP with order constraints;Annals of Operations Research;2024-05-06

3. Scalable Multi-Robot Task Allocation Using Graph Deep Reinforcement Learning with Graph Normalization;Electronics;2024-04-19

4. Genetic algorithm to the bi-objective multiple travelling salesman problem;Alexandria Engineering Journal;2024-03

5. Genetic Algorithm Based on Opposite Chromosome Multiple Genetic Operations Combined with Task Load Balancing;Journal of Physics: Conference Series;2024-03-01