Iteration strategy and ts effect towards the performance of population based metaheuristics

Nor Azlina, Ab. Aziz and Nor Hidayati, Abdul Aziz and Azlan, Abd Aziz and Tasiransurini, Abdul Rahman and Wan Zakiah, Wan Ismail and Zuwairie, Ibrahim (2020) Iteration strategy and ts effect towards the performance of population based metaheuristics. In: Proceeding - 2020 IEEE 8th Conference on Systems, Process and Control, ICSPC 2020. 8th IEEE Conference on Systems, Process and Control, ICSPC 2020 , 11 - 12 December 2020 , Melaka. pp. 58-63.. ISBN 978-172818861-4 (Published)

	Pdf Iteration strategy and its effect towards the performance.pdf Restricted to Repository staff only Download (373kB) | Request a copy
Preview	Pdf Iteration strategy and its effect towards the performance of population based metaheuristics_ABS.pdf Download (216kB) | Preview

Abstract

Metaheuristics algorithms solve optimization problems by repeating a set of procedures. The algorithms can be categorized based on number of agents, either single agent algorithms which are also known as single solution metaheuristics or multi agents algorithms, also known as population-based metaheuristics. In single solution based algorithms, the steps are executed one by one by the single search agent. However, the sequence of the procedures execution with respect to members of a population becomes an issue in population-based algorithms. This issue is governed by iteration strategy, which affects the flow of information within the population. The effect of iteration strategy is studied here. This is an important issue to be considered when designing a new population-based metaheuristic. Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. Here, the effect of iteration strategy is studied using the CEC2014's benchmark functions. The finding shows that iteration strategy can influence the performance of an algorithm and the best iteration strategy is unique to its parent algorithm. A researcher developing a new population-based algorithm need to identify the best strategy so that the performance of the algorithm proposed is maximized.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Asynchronous update; Iteration strategy; Population-based metaheuristics; Synchronous update
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures
Faculty/Division:	Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	30 Oct 2024 04:45
Last Modified:	30 Oct 2024 04:45
URI:	http://umpir.ump.edu.my/id/eprint/42432
Download Statistic:	View Download Statistics

Actions (login required)

View Item