Title: Prey predator algorithm with adaptive step length

Authors: Surafel Luleseged Tilahun; Jean Medard T. Ngnotchouye

Addresses: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, Pietermaritzburg, South Africa ' School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, Pietermaritzburg, South Africa

Abstract: Prey predator algorithm is a swarm-based metaheuristic algorithm inspired by the interaction between a predator and its prey. The worst performing solution from the solution set is called a predator, the best preforming solution is called best prey and the rest are called ordinary prey. The predator focuses on exploration while the best prey totally focuses on exploitation. Parameter assignments, especially step length, plays an important role in rapid convergence of the solution to the optimal solution. If the step length is too short, the algorithm will take more time to converge whereas if it is too big, then the algorithm will oscillates by jumping over the solution, making it hard to obtain the desired quality of solution. In this paper, adaptive step length for prey predator algorithm will be used to produce a rapid convergence. The study is also supported by simulation results with appropriate statistical analysis.

Keywords: prey predator algorithm; PPA; metaheuristics; bio-inspired computation; adaptive step length; convergence; group hunting; optimisation; multimodal problem; exploration; exploitation; simulation.

DOI: 10.1504/IJBIC.2016.078663

International Journal of Bio-Inspired Computation, 2016 Vol.8 No.4, pp.195 - 204

Received: 29 Aug 2015
Accepted: 14 May 2016
Published online: 30 Aug 2016 *

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