Muthana, Shatha Abdulhadi and Ku Mahamud, Ku Ruhana (2023) Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm. Journal of Information and Communication Technology, 22 (2). pp. 149-181. ISSN 2180-3862

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Abstract

In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. For optimal maintenance scheduling with low cost, high reliability, and low violation, the parameter values of the PACS algorithm were tuned using the Taguchi and Gray Relational Analysis (Taguchi-GRA) method through search-based approach. The new parameter values were tested on two systems. i.e., 26- and 36-unit systems for window with operational hours [3000-5000]. The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. These values can be benchmarked in solving multi-objective GMS problems using the multi-objective PACS algorithm and its variants.

Item Type:	Article
Uncontrolled Keywords:	Optimization, Scheduling, Taguchi method, Gray Relational Analysis, Generator maintenance
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs Nurin Jazlina Hamid
Date Deposited:	19 Apr 2023 01:39
Last Modified:	19 Apr 2023 01:39
URI:	https://repo.uum.edu.my/id/eprint/29399

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