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: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2015
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| Online Access: | http://journalarticle.ukm.my/9733/1/jqma-11-2-paper3.pdf http://journalarticle.ukm.my/9733/ http://www.ukm.my/jqma/jqma11_2a.html |
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| Summary: | 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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