June 26 - 30, 2004 Saturday to Wednesday Seattle, Washington, USA
SOE - Self-Organization on Representations for Genetic and Evolutionary Algorithms
Solving Rotated Multi-objective Optimization Problems Using Di?erential Evolution
Antony W. Iorio Xiaodong Li
This paper demonstrates that the self-adaptive technique of Differential Evolution (DE) can be used for solving epistatic multi-objective optimization problems. The real-coded crossover and mutation rates within the NSGA-II have been replaced with a simple Differential Evolution scheme and results are reported on a rotated problem which has presented difficulties using existing Multi-objective Evolutionary Algorithms. The Differential Evolution variant of NSGA-II has demonstrated rotational invariance and superior performance over the NSGA-II on this problem.