Differential evolution for multi-objective optimization with self adaptation

In the paper an adapted version of the differential evolution algorithm has been created to solve a multi-objective optimization problem. Multi-objective Differential Evolution Algorithm using vector differences for perturbing the vector population with self adaptation is introduced. Through the combination of mutation strategies and self adaptation of crossover and differentiation constants the proposed MO algorithm performs better than the one with the simple DE scheme in terms of computation speed and quality of the generated multi-objective non-dominated solutions.