Multi-strategy competitive-cooperative co-evolutionary algorithm and its application
X Zhou, X Cai, H Zhang, Z Zhang, T **, H Chen… - Information …, 2023 - Elsevier
In order to effectively solve multi-objective optimization problems (MOPs) and fully balance
uniformity and convergence, a multi-strategy competitive-cooperative co-evolutionary …
uniformity and convergence, a multi-strategy competitive-cooperative co-evolutionary …
A survey of evolutionary algorithms for multi-objective optimization problems with irregular Pareto fronts
Evolutionary algorithms have been shown to be very successful in solving multi-objective
optimization problems (MOPs). However, their performance often deteriorates when solving …
optimization problems (MOPs). However, their performance often deteriorates when solving …
Review of the research landscape of multi-criteria evaluation and benchmarking processes for many-objective optimization methods: coherent taxonomy, challenges …
Evaluation and benchmarking of many-objective optimization (MaOO) methods are
complicated. The rapid development of new optimization algorithms for solving problems …
complicated. The rapid development of new optimization algorithms for solving problems …
A many-objective particle swarm optimization with grid dominance ranking and clustering
The existing MOPSOs face a great challenge in dealing with many-objective problems, due
to the low discriminability of particles in many-objective spaces, which will affect the …
to the low discriminability of particles in many-objective spaces, which will affect the …
On the utilization of pair-potential energy functions in multi-objective optimization
In evolutionary multi-objective optimization (EMO), the pair-potential energy functions (PPFs)
have been used to construct diversity-preserving mechanisms to improve Pareto front …
have been used to construct diversity-preserving mechanisms to improve Pareto front …
A survey of meta-heuristic algorithms in optimization of space scale expansion
J Zhang, L Wei, Z Guo, H Sun, Z Hu - Swarm and Evolutionary …, 2024 - Elsevier
Optimization problem of space scale expansion widely exists in practical applications, such
as transportation, logistics, scheduling, social networks, etc. According to different expansion …
as transportation, logistics, scheduling, social networks, etc. According to different expansion …
A weight vector generation method based on normal distribution for preference-based multi-objective optimization
In researching multi-objective evolutionary algorithms (MOEAs), the decision-maker (DM)
may not need the entire Pareto optimal front searched and may only be interested in the …
may not need the entire Pareto optimal front searched and may only be interested in the …
Hypervolume-Based Cooperative Coevolution with Two Reference Points for Multi-Objective Optimization
An important issue in hypervolume-based evolutionary multi-objective optimization (EMO)
algorithms is the specification of a reference point for hypervolume calculation. However, its …
algorithms is the specification of a reference point for hypervolume calculation. However, its …
Cooperative-competitive two-stage game mechanism assisted many-objective evolutionary algorithm
Z Zhang, H Wang, W Zhang, Z Cui - Information Sciences, 2023 - Elsevier
It is critical to maintain significant convergence and diversity in many-objective optimization
problems (MaOPs) for the performance of many-objective evolutionary algorithms …
problems (MaOPs) for the performance of many-objective evolutionary algorithms …
A many-objective evolutionary algorithm based on rotation and decomposition
Evolutionary algorithms have shown their promise in addressing multiobjective problems
(MOPs). However, the Pareto dominance used in multiobjective optimization loses its …
(MOPs). However, the Pareto dominance used in multiobjective optimization loses its …