A surrogate-assisted evolutionary algorithm based on multi-population clustering and prediction for solving computationally expensive dynamic optimization problems.
Luda ZhaoYihua HuBin WangXiaoping JiangChunsheng LiuChao ZhengPublished in: Expert Syst. Appl. (2023)
Keyphrases
- computationally expensive
- dynamic optimization problems
- evolutionary algorithm
- multi population
- genetic algorithm
- dynamic optimization
- evolutionary computation
- multi objective
- optimization problems
- differential evolution
- fitness function
- computationally efficient
- clustering algorithm
- multi objective optimization
- k means
- clustering method
- simulated annealing
- evolution strategy
- genetic programming
- optimization method
- mutation operator
- function optimization
- combinatorial optimization
- candidate solutions
- machine learning
- test functions
- crossover operator