Weighted superposition attraction algorithm for combinatorial optimization

作者：

Highlights：

• The first application of WSA algorithm to combinatorial optimization.

• A novel approach to superposition determination.

• A direct approach to solution coding and encoding for permutation type vectors.

• Integrated use of random walks and opposition based learning strategies.

• Based on several performance measures many published results are outperformed.

摘要

•The first application of WSA algorithm to combinatorial optimization.•A novel approach to superposition determination.•A direct approach to solution coding and encoding for permutation type vectors.•Integrated use of random walks and opposition based learning strategies.•Based on several performance measures many published results are outperformed.

论文关键词：Metaheuristics,Weighted superposition attraction,Random walk,Opposition based learning,Resource constrained project scheduling,Permutation flow shop scheduling

论文评审过程：Received 11 March 2019, Revised 4 July 2019, Accepted 4 July 2019, Available online 5 July 2019, Version of Record 19 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.07.009