TGSR: the great salmon run optimisation algorithm

被引:2
|
作者
Fathi, Alireza [1 ]
Mozaffari, Ahmad [1 ]
机构
[1] Babol Univ Technol, Dept Mech Engn, POB 484, Babol Sar, Mazandaran, Iran
关键词
great salmon run; TGSR; metaheuristics; stochastic optimisation; natural inspiration;
D O I
10.1504/IJCAT.2014.062357
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The purpose of the current research is to introduce a novel heuristic natural inspired optimisation algorithm based on the annual migration of salmons and common the menaces that lie behind their pathways. This simulation provides a powerful tool for optimising complex multi-dimensional and multi-modal problems. For demonstrating the high robustness and acceptable quality of the great salmon run (TGSR), it is compared with some well-known optimisation techniques such as genetic algorithm (GA), particle swarm optimisation (PSO) and artificial bee colony (ABC). Simulated experiments are conducted on several benchmark problems and one real-life engineering problem. The obtained results confirm the high performance of the proposed method in both robustness and quality for different optimisation problems.
引用
收藏
页码:192 / 206
页数:15
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