Multimodal multi-objective problems (MMOPs) commonly arise in the real world where
distant solutions in decision space correspond to very similar objective values. To obtain …

Multimodal multiobjective optimization aims to find all Pareto optimal solutions, including
overlap** solutions in the objective space. Multimodal multiobjective optimization has …

This paper presents a new particle swarm optimizer for solving multimodal multiobjective
optimization problems which may have more than one Pareto-optimal solution …

Multimodal multiobjective problems (MMOPs) commonly arise in real-world situations where
distant solutions in decision space share a very similar objective value. Traditional …

As an effective evolutionary algorithm, particle swarm optimization (PSO) has been widely
used to solve single or multi-objective optimization problems. However, the performance of …

Multimodal multiobjective problems (MMOPs) arise frequently in the real world, in which
multiple Pareto-optimal solution (PS) sets correspond to the same point on the Pareto front …

This paper proposes a multimodal multiobjective Differential Evolution optimization
algorithm (MMODE). The technique is conceived for deployment on problems with a Pareto …

In the multimodal multi-objective optimization problems (MMOPs), there may exist two or
multiple equivalent Pareto optimal sets (PS) with the same Pareto Front (PF). The difficulty of …

This paper proposes a self-organized speciation based multi-objective particle swarm
optimizer (SS-MOPSO) to locate multiple Pareto optimal solutions for solving multimodal …

Most existing multiobjective evolutionary algorithms aim at approximating the Pareto front
(PF), which is the distribution of the Pareto-optimal solutions in the objective space. In many …