Multi-objective equilibrium optimizer: framework and development for solving multi-objective optimization problems

ABSTRACT This paper proposes a new Multi-Objective Equilibrium Optimizer (MOEO) to handle complex optimization problems, including real-world engineering design problems. The (EO) is recently reported physics-based metaheuristic algorithm, and it has been inspired by the models used predict equilibrium state dynamic state. A similar procedure utilized in MOEO combining different target search space. crowding distance mechanism employed algorithm balance exploitation exploration phases as progresses. In addition, non-dominated sorting strategy also merged with preserve population diversity considered crucial problem multi-objective algorithms. An archive an update function uphold improve coverage of Pareto optimal solutions. performance validated for 33 contextual problems 6 constrained, 12 unconstrained, 15 practical constrained non-linear result obtained proposed compared other state-of-the-art quantitative qualitative results indicate that provides more competitive outcomes than From all benchmark efficiency, robustness, ability solve are well defined clarified. further supported extra online service guideline at https://premkumarmanoharan.wixsite.com/mysite.