A Memetic Hunting Search Algorithm for the Traveling Salesman Problem

被引：0
|
作者：
Agharghor, Amine [1 ]
Riffi, Mohammed Essaid [1 ]
Chebihi, Faycal [1 ]
机构：
[1] Chouaib Doukkali Univ, Fac Sci, Dept Comp Sci, Lab LAROSERIE, El Jadida, Morocco
来源：
2016 4TH IEEE INTERNATIONAL COLLOQUIUM ON INFORMATION SCIENCE AND TECHNOLOGY (CIST) | 2016年
关键词：
Hunting Search Algorithm; 2-Opt local search; Traveling Salesman problem; Combinatorial Optimization; Memetic Algorithms;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Since 1930s, traveling salesman problem is still one of the most studied problems in optimization. It started to be used as a benchmark for the new optimization methods that solves the combinatorial optimization problem NP-hard. This paper proposes an assessment of a memetic Hunting Search algorithm that uses a 2-Opt local search for solving the traveling salesman problem. Hunting Search is an evolutionary algorithm inspired by the method of group hunting of predatory animals. To show the quality of the memetic algorithm, it has been checked on a set of ten benchmark TSPLib instances and it outperforms the results obtained with previous Hunting Search algorithm.
引用
收藏
页码：206 / 209
页数：4
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