Self-adaptive multi-objective differential evolutionary algorithm based on decomposition
Lingyu Chen, Beizhan Wang, Weiqiang Liu, Jiajun Wang · 2016
On the basis of MOEA/D-DE algorithm, the introduction of the concept of a self-adaptive differential evolution algorithm, named self-adaptive multi-objective differential evolutionary algorithm based on decomposition (SAMODEA/D). This algorithm enhances the local search algorithm in the case of maintaining the diversity of the population, while effectively avoids “premature convergence” and the occurrence of “local optimum” situation, a good solution to keep balance between the global search and local development. The experimental results have illustrated the effectiveness of the proposed algorithm.