A study on an extended Prey-Predator algorithm

Metaheuristic algorithms are approximate solution methods for optimisation problems which try to improve the quality of solution at hand iteratively in a random way. In recent years, various studies have been conducted in forming new metaheuristic algorithms and modifying or improving existing al...

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Main Authors: Hong, Choon Ong, Chia, Jiun Ng
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2015
Online Access:http://journalarticle.ukm.my/9733/
http://journalarticle.ukm.my/9733/1/jqma-11-2-paper3.pdf
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author Hong, Choon Ong
Chia, Jiun Ng
author_facet Hong, Choon Ong
Chia, Jiun Ng
author_sort Hong, Choon Ong
building UKM Institutional Repository
collection Online Access
description Metaheuristic algorithms are approximate solution methods for optimisation problems which try to improve the quality of solution at hand iteratively in a random way. In recent years, various studies have been conducted in forming new metaheuristic algorithms and modifying or improving existing algorithms to enhance the performance in optimal solution search. In this study, we focus on extending an existing algorithm Prey-Predator algorithm proposed by Tilahun and Ong. Prey-Predator algorithm is a metaheuristic algorithm inspired by interaction between prey and predator among animals. The algorithm imitates the way a predator runs after and hunts its preys where each prey tries to stay with the pack trying to search for hiding place and run away from the predator. In extension of Prey-Predator algorithm, the number of both best preys and predators are increased resulting in a more reasonably exploitation and exploration so that multiple solutions can be achieved. The simulation of nmPPA is carried on ten selected benchmarks test function. nmPPA aimed to solve the problem of objective values being trapped in local optimum and to find multiple solutions at the same time.
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spelling oai:generic.eprints.org:97332016-12-14T06:50:40Z http://journalarticle.ukm.my/9733/ A study on an extended Prey-Predator algorithm Hong, Choon Ong Chia, Jiun Ng Metaheuristic algorithms are approximate solution methods for optimisation problems which try to improve the quality of solution at hand iteratively in a random way. In recent years, various studies have been conducted in forming new metaheuristic algorithms and modifying or improving existing algorithms to enhance the performance in optimal solution search. In this study, we focus on extending an existing algorithm Prey-Predator algorithm proposed by Tilahun and Ong. Prey-Predator algorithm is a metaheuristic algorithm inspired by interaction between prey and predator among animals. The algorithm imitates the way a predator runs after and hunts its preys where each prey tries to stay with the pack trying to search for hiding place and run away from the predator. In extension of Prey-Predator algorithm, the number of both best preys and predators are increased resulting in a more reasonably exploitation and exploration so that multiple solutions can be achieved. The simulation of nmPPA is carried on ten selected benchmarks test function. nmPPA aimed to solve the problem of objective values being trapped in local optimum and to find multiple solutions at the same time. Penerbit Universiti Kebangsaan Malaysia 2015-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/9733/1/jqma-11-2-paper3.pdf Hong, Choon Ong and Chia, Jiun Ng (2015) A study on an extended Prey-Predator algorithm. Journal of Quality Measurement and Analysis, 11 (2). pp. 17-29. ISSN 1823-5670 http://www.ukm.my/jqma/jqma11_2a.html
spellingShingle Hong, Choon Ong
Chia, Jiun Ng
A study on an extended Prey-Predator algorithm
title A study on an extended Prey-Predator algorithm
title_full A study on an extended Prey-Predator algorithm
title_fullStr A study on an extended Prey-Predator algorithm
title_full_unstemmed A study on an extended Prey-Predator algorithm
title_short A study on an extended Prey-Predator algorithm
title_sort study on an extended prey-predator algorithm
url http://journalarticle.ukm.my/9733/
http://journalarticle.ukm.my/9733/
http://journalarticle.ukm.my/9733/1/jqma-11-2-paper3.pdf