A survey on learnable evolutionary algorithms for scalable multiobjective optimization
Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
Expensive multiobjective optimization by relation learning and prediction
Expensive multiobjective optimization problems pose great challenges to evolutionary
algorithms due to their costly evaluation. Building cheap surrogate models to replace the …
algorithms due to their costly evaluation. Building cheap surrogate models to replace the …
Surrogate-assisted differential evolution with adaptive multisubspace search for large-scale expensive optimization
Real-world industrial engineering optimization problems often have a large number of
decision variables. Most existing large-scale evolutionary algorithms (EAs) need a large …
decision variables. Most existing large-scale evolutionary algorithms (EAs) need a large …
A pairwise comparison based surrogate-assisted evolutionary algorithm for expensive multi-objective optimization
Multi-objective optimization problems in many real-world applications are characterized by
computationally or economically expensive objectives, which cannot provide sufficient …
computationally or economically expensive objectives, which cannot provide sufficient …
Evolutionary algorithm with individual-distribution search strategy and regression-classification surrogates for expensive optimization
Surrogate-assisted evolutionary algorithms (SAEAs) with prescreening model management
strategies show great potential in handling expensive optimization problems (EOPs) …
strategies show great potential in handling expensive optimization problems (EOPs) …
Reference vector-assisted adaptive model management for surrogate-assisted many-objective optimization
Acquisition functions for surrogate-assisted many-objective optimization require a delicate
balance between convergence and diversity. However, the conflicting nature between many …
balance between convergence and diversity. However, the conflicting nature between many …
Surrogate-assisted many-objective optimization of building energy management
Building energy management usually involves a number of objectives, such as investment
costs, thermal comfort, system resilience, battery life, and many others. However, most …
costs, thermal comfort, system resilience, battery life, and many others. However, most …
An expensive many-objective optimization algorithm based on efficient expected hypervolume improvement
The expected hypervolume improvement (EHVI) is one of the most popular infill criteria for
multiobjective optimization problems. Although it has a significant advantage in exploring …
multiobjective optimization problems. Although it has a significant advantage in exploring …
Enhancing SAEAs with unevaluated solutions: a case study of relation model for expensive optimization
Surrogate-assisted evolutionary algorithms (SAEAs) hold significant importance in resolving
expensive optimization problems. Extensive efforts have been devoted to improving the …
expensive optimization problems. Extensive efforts have been devoted to improving the …
A steady-state algorithm for solving expensive multiobjective optimization problems with nonparallelizable evaluations
Expensive multiobjective optimization problems (EMOPs) refer to those wherein evaluation
of each candidate solution incurs a significant cost. To solve such problems within a limited …
of each candidate solution incurs a significant cost. To solve such problems within a limited …