Marine Predator Algorithm MPA Review: Marine Predator-Inspired Optimization and Its Applications to Optimization Problems
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Abstract
In recent years, the Marine Predator Algorithm (MPA) has emerged as a powerful tool in the field of metaheuristic optimization, an algorithm inspired by the behavior of marine predators in the natural environment. This algorithm is based on three main strategies to simulate what happens between predators and prey, which gives a strong balance between the exploration process and the exploitation process. This paper attempts to review the most important improvements, modifications and applications of the MPA algorithm in several fields. Compared to algorithms such as PSO, SMA and other algorithms, MPA has proven its effectiveness and strength, especially in improving the speed and accuracy in reaching optimal solutions. Despite its successes, MPA faces some challenges in certain problems, such as the need for additional modifications to improve its performance in more complex environments. In this context, we discuss future directions for developing this algorithm and expanding its use in new fields.
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