A Survey on Evolutionary Constrained Multiobjective Optimization
Zhengzhou University · Zhongyuan University of Technology · +1 more institution
Abstract
Handling constrained multiobjective optimization problems (CMOPs) is extremely challenging, since multiple conflicting objectives subject to various constraints require to be simultaneously optimized. To deal with CMOPs, numerous constrained multiobjective evolutionary algorithms (CMOEAs) have been proposed in recent years, and they have achieved promising performance. However, there has been few literature on the systematic review of the related studies currently. This article provides a comprehensive survey for evolutionary constrained multiobjective optimization. We first review a large number of CMOEAs through categorization and analyze their advantages and drawbacks in each category. Then, we summarize…
Citation impact
- FWCI
- 52.50
- Percentile
- 100%
- References
- 208
Authors
8Topics & keywords
- Multi-objective optimization
- Benchmark (surveying)
- Evolutionary algorithm
- Computer science
- Evolutionary computation
- Mathematical optimization
- Optimization problem
- Constraint (computer-aided design)