A multi-objective hyper-heuristic based on choice function

作者：

Highlights：

• A learning selection hyper-heuristic is proposed for multi-objective optimization.

• A choice function utilized within the framework for multi-objective optimization.

• Three MOEAs (NSGAII, SPEA2, and MOGA) are mixes and exploited their strengths.

• The proposed method performs better than three MOEAs and some other approaches.

• The proposed method is tested on a generic benchmark and a real-world problem.

摘要

•A learning selection hyper-heuristic is proposed for multi-objective optimization.•A choice function utilized within the framework for multi-objective optimization.•Three MOEAs (NSGAII, SPEA2, and MOGA) are mixes and exploited their strengths.•The proposed method performs better than three MOEAs and some other approaches.•The proposed method is tested on a generic benchmark and a real-world problem.

论文关键词：Hyper-heuristic,Metaheuristic,Evolutionary algorithm,Multi-objective optimization

论文评审过程：Available online 26 January 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.12.050