Adaptive predator prey algorithm for many objective optimization.

ABSTRACT: Balancing diversity and convergence among solutions in many-objective optimization is challenging, particularly in high-dimensional spaces with conflicting objectives. This paper presents the Many-Objective Marine Predator Algorithm (MaOMPA), an adaptation of the Marine Predators Algorithm (MPA) specifically enhanced for many-objective optimization tasks. MaOMPA integrates an elitist, non-dominated sorting and crowding distance mechanism to maintain a well-distributed set of solutions on the Pareto front. MaOMPA improves upon traditional metaheuristic methods by achieving a robust balance between exploration and exploitation using the predator-prey interaction model. The algorithm underwent evaluation on various benchmarks together with complex real-world engineering problems where it show

SUBMITTER: Mashru N 

PROVIDER: S-EPMC11993708 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature