An Efficient Marine Predators Algorithm for Solving Multi-Objective Optimization Problems: Analysis and Validations

Recently, a new strong optimization algorithm called marine predators (MPA) has been proposed for tackling the single-objective problems and could dramatically fulfill good outcomes in comparison to other compared algorithms. Those dramatic outcomes, addition our recently-proposed strategies helping meta-heuristic algorithms fulfilling better multi-objective problems, motivate us make comprehensive study see performance of MPA alone with those problems. Specifically, This paper proposes four variants predators' solving The first version, (MMPA) is based on behavior finding their prey. In second novel strategy dominance strategy-based exploration-exploitation (DSEE) effectively incorporated MMPA relate exploration exploitation phase solutions-this version M-MMPA. DSEE counts number dominated solutions each solution-the high undergo an phase; others small phase. third integrates M-MMPA Gaussian-based mutation, which uses Gaussian distribution-based search optimal solution. fourth Nelder-Mead simplex method (M-MMPA-NMM) at start process construct front non-dominated that will help find more solutions. effectiveness versions validated large set theoretical practical For all cases, its are shown be superior well-known