Comparison of Swarm and Graph Algorithms for Solving Travelling Salesman Problems

被引：0
|
作者：
Eggenschwiler, Stefan [1 ]
Spahic-Bogdanovic, Maja [1 ]
Hanne, Thomas [1 ]
Dornberger, Rolf [2 ]
机构：
[1] Univ Appl Sci & Arts Northwestern Switzerland, Olten, Switzerland
[2] Univ Appl Sci & Arts Northwestern Switzerland, Basel, Switzerland
来源：
2020 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2020) | 2020年
关键词：
travelling salesman problem; nature-inspired algorithms; swarm intelligence; combinatorial optimization;
D O I：
10.1109/iscmi51676.2020.9311558
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we compare different nature-inspired, swarm algorithms (4 variants of ACO and PSO) and five graph algorithms for solving the travelling salesman problem based on defined key metrics. We focus on describing the experimental setup including input data and the outline of the metrics applied in the analysis part. The aim is to compare the performance of metaheuristics (nature-based) algorithms with traditional algorithms used for solving travelling salesman problems (TSP).
引用
收藏
页码：1 / 7
页数：7
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