A survey on learnable evolutionary algorithms for scalable multiobjective optimization

S Liu, Q Lin, J Li, KC Tan - IEEE Transactions on Evolutionary …, 2023 - ieeexplore.ieee.org
Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …

Inverse model and adaptive neighborhood search based cooperative optimizer for energy-efficient distributed flexible job shop scheduling

S Cao, R Li, W Gong, C Lu - Swarm and Evolutionary Computation, 2023 - Elsevier
Solving the energy-efficient distributed flexible job shop scheduling problem (EEDFJSP)
obtains increased attention. However, most previous studies barely considered the large …

MOCPSO: A multi-objective cooperative particle swarm optimization algorithm with dual search strategies

Y Zhang, B Li, W Hong, A Zhou - Neurocomputing, 2023 - Elsevier
Particle swarm optimization (PSO) is a widely embraced meta-heuristic approach to tackling
the complexities of multi-objective optimization problems (MOPs), renowned for its simplicity …

A modified competitive swarm optimizer guided by space sampling for large-scale multi-objective optimization

X Gao, F He, F Wang, X Wang - Swarm and Evolutionary Computation, 2024 - Elsevier
Multi-objective evolutionary algorithms have demonstrated promising performance in
solving multi/many-objective problems. However, their performance decreases sharply …

A fast nondominated sorting-based MOEA with convergence and diversity adjusted adaptively

X Gao, F He, S Zhang, J Luo, B Fan - The Journal of Supercomputing, 2024 - Springer
In the past few decades, to solve the multi-objective optimization problems, many multi-
objective evolutionary algorithms (MOEAs) have been proposed. However, MOEAs have a …

A flexible ranking-based competitive swarm optimizer for large-scale continuous multi-objective optimization

X Gao, S Song, H Zhang, Z Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Due to the curse of dimensionality, the search efficiency of existing operators in large-scale
decision space deteriorates dramatically. The competitive swarm optimizer (CSO)-based …

Pareto optimization with small data by learning across common objective spaces

CS Tan, A Gupta, YS Ong, M Pratama, PS Tan… - Scientific Reports, 2023 - nature.com
In multi-objective optimization, it becomes prohibitively difficult to cover the Pareto front (PF)
as the number of points scales exponentially with the dimensionality of the objective space …