Title: TGSR: the great salmon run optimisation algorithm

Authors: Alireza Fathi; Ahmad Mozaffari

Addresses: Department of Mechanical Engineering, Babol University of Technology, Babol, Mazandaran, P.O. Box 484, Iran ' Department of Mechanical Engineering, Babol University of Technology, Babol, Mazandaran, P.O. Box 484, Iran

Abstract: 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.

Keywords: great salmon run; TGSR; metaheuristics; stochastic optimisation; natural inspiration; bio-inspired computation; salmon migration; simulation; genetic algorithms; particle swarm optimisation; PSO; artificial bee colony.

DOI: 10.1504/IJCAT.2014.062357

International Journal of Computer Applications in Technology, 2014 Vol.49 No.3/4, pp.192 - 206

Available online: 05 Jun 2014 *

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