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.
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