Extended Prey-Predator Algorithm with a Group Hunting Scenario
Surafel Luleseged Tilahun, Hong Choon Ong, Jean Medard T. Ngnotchouye · Advances in Operations Research · 2016
Prey-predator algorithm (PPA) is a metaheuristic algorithm inspired by the interaction between a predator and its prey. In the algorithm, the worst performing solution, called the predator, works as an agent for exploration whereas the better performing solution, called the best prey, works as an agent for exploitation. In this paper, PPA is extended to a new version callednm-PPA by modifying the number of predators and also best preys. Innm-PPA, there will benbest preys andmpredators. Increasing the value ofnincreases the exploitation and increasing the value ofmincreases the exploration property of the algorithm. Hence, it is possible to adjust the degree of exploration and exploitation as needed by adjusting the values ofnandm. A guideline on setting parameter values will also be discussed along with a new way of measuring performance of an algorithm for multimodal problems. A simulation is also done to test the algorithm using well known eight benchmark problems of different properties and different dimensions ranging from two to twelve showing thatnm-PPA is found to be effective in achieving multiple solutions in multimodal problems and also has better ability to overcome being trapped in local optimal solutions.