Multimodal multi-objective optimization: Comparative study of the state-of-the-art
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 …
distant solutions in decision space correspond to very similar objective values. To obtain …
Hierarchy ranking method for multimodal multiobjective optimization with local Pareto fronts
Multimodal multiobjective problems (MMOPs) commonly arise in real-world situations where
distant solutions in decision space share a very similar objective value. Traditional …
distant solutions in decision space share a very similar objective value. Traditional …
Differential evolution using improved crowding distance for multimodal multiobjective optimization
In multiobjective optimization, the relationship between decision space and objective space
is generally assumed to be a one-to-one map**, but it is not always the case. In some …
is generally assumed to be a one-to-one map**, but it is not always the case. In some …
A modified particle swarm optimization for multimodal multi-objective optimization
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 …
used to solve single or multi-objective optimization problems. However, the performance of …
Weighted indicator-based evolutionary algorithm for multimodal multiobjective optimization
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 …
multiple Pareto-optimal solution (PS) sets correspond to the same point on the Pareto front …
Multimodal multiobjective evolutionary optimization with dual clustering in decision and objective spaces
This article suggests a multimodal multiobjective evolutionary algorithm with dual clustering
in decision and objective spaces. One clustering is run in decision space to gather nearby …
in decision and objective spaces. One clustering is run in decision space to gather nearby …
Competition-driven multimodal multiobjective optimization and its application to feature selection for credit card fraud detection
Feature selection has been considered as an effective method to solve imbalanced
classification problems. It can be formulated as a multiobjective optimization problem (MOP) …
classification problems. It can be formulated as a multiobjective optimization problem (MOP) …
A clustering-based differential evolution algorithm for solving multimodal multi-objective optimization problems
Abstract Multimodal Multi-objective Optimization Problems (MMOPs) refer to the problems
that have multiple Pareto-optimal solution sets in decision space corresponding to the same …
that have multiple Pareto-optimal solution sets in decision space corresponding to the same …
Grid search based multi-population particle swarm optimization algorithm for multimodal multi-objective optimization
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 …
multiple equivalent Pareto optimal sets (PS) with the same Pareto Front (PF). The difficulty of …
[PDF][PDF] Problem definitions and evaluation criteria for the CEC 2019 special session on multimodal multiobjective optimization
In multiobjective optimization problems, there may exist two or more global or local Pareto
optimal sets (PSs) and some of them may correspond to the same Pareto Front (PF). These …
optimal sets (PSs) and some of them may correspond to the same Pareto Front (PF). These …