Improving the state-of-the-art in the Traveling Salesman Problem: An Anytime Automatic Algorithm Selection

作者：

Highlights：

• A new metaheuristic for the TSP based on Automatic Algorithm Selection is proposed.

• We consider the anytime nature of the solution computation by the solvers in our work.

• A spatial representation of instances is presented, avoiding calculation of features.

• Our approach outperforms state-of-the-art solvers in public data sets.

摘要

•A new metaheuristic for the TSP based on Automatic Algorithm Selection is proposed.•We consider the anytime nature of the solution computation by the solvers in our work.•A spatial representation of instances is presented, avoiding calculation of features.•Our approach outperforms state-of-the-art solvers in public data sets.

论文关键词：Combinatorial optimization,TSP,Algorithm selection problem,Anytime behavior approach

论文评审过程：Received 16 March 2021, Revised 8 September 2021, Accepted 19 September 2021, Available online 6 October 2021, Version of Record 6 October 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115948