Title: Finally, which meta-heuristic algorithm is the best one?

Authors: Elham Shadkam; Samane Safari; Saba Saberi Abdollahzadeh

Addresses: Department of Industrial Engineering, Faculty of Engineering, Khayyam University, Mashhad, Iran ' Department of Industrial Engineering, Faculty of Engineering, Khayyam University, Mashhad, Iran ' Department of Industrial Engineering, Faculty of Engineering, Khayyam University, Mashhad, Iran

Abstract: This paper is conducted to rank the six meta-heuristic algorithms such as the genetic, ant colony optimisation, tabu search, particle swarm optimisation, imperialist competitive, and simulated annealing algorithm and choose the most efficient algorithm among them, concerning collected information. Accordingly, three multi-criteria decision-making methods, including the analytical hierarchy process (AHP), TOPSIS, and AHP-TOPSIS methods are used. Criteria for comparing algorithms are selected based on the capability of each algorithm and the issues that are necessary to solve each problem. The result of the TOPSIS method indicates the superiority and efficiency of the tabu search algorithm. However, the analytical hierarchy process presents the ant colony algorithm as the best algorithm. Also, in the AHP-TOPSIS method, the best meta-heuristic algorithm is genetic. Finally, according to the results obtained from all three methods and the use of the combined compromise solution method (CoCoSo), the genetic algorithm is selected as the best algorithm.

Keywords: meta-heuristic algorithms; TOPSIS; analytical hierarchy process; AHP; multi-criteria decision-making; combined compromise solution method; CoCoSo.

DOI: 10.1504/IJDSRM.2021.117555

International Journal of Decision Sciences, Risk and Management, 2021 Vol.10 No.1/2, pp.32 - 50

Received: 26 Aug 2020
Accepted: 09 Oct 2020

Published online: 10 Sep 2021 *

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