Rotationally Invariant Crossover Operators in Evolutionary Multi-objective Optimization
Rotationally Invariant Crossover Operators in Evolutionary Multi-objective Optimization
复制标题
进化多目标优化中的旋转不变交叉算子
DOI:
10.1007/11903697_40
复制
发表时间:
2006
期刊:
影响因子:
--
通讯作者:
Xiaodong Li
中科院分区:
文献类型:
--
作者:
A. Iorio;Xiaodong Li
Multi-objective problems with parameter interactions can present difficulties to many optimization algorithms. We have investigated the behaviour of Simplex Crossover (SPX), Unimodal Normally Distributed Crossover (UNDX), Parent-centric Crossover (PCX), and Differential Evolution (DE), as possible alternatives to the Simulated Binary Crossover (SBX) operator within the NSGA-II (Non-dominated Sorting Genetic Algorithm II) on four rotated test problems exhibiting parameter interactions. The rotationally invariant crossover operators demonstrated improved performance in optimizing the problems, over a non-rotationally invariant crossover operator.