Multi-objective Aquila Optimizer (MOAO)

An efficient Aquila Optimization (AO) algorithm based on grid technology for solving multimodal multi-objective optimization problems

First, the basic AO algorithm is extended to a multi-objective version using the non-dominated fast sorting technique and the external file mechanism, which allows the algorithm to find the set of Pareto optimal solutions for multi-objective optimization problems (MOOP). Second, the grid concept is used to select possible subregions in the decision space, thus generating several populations, thus maintaining population diversity during the iterative research process. Finally, the proposed algorithm is tested on 24 standard multimodal multi-objective functions to evaluate its performance.