Anytime automatic algorithm selection for knapsack

作者：

Highlights：

• New “Anytime” Framework for Automatic Algorithm Selection.

• Application of the Anytime Automatic Algorithm Selection Framework to Knapsack.

• 3 Machine Learning Models proposed for the Problem.

• Knapsack Instances, Features and Solvers Behavior publicly available.

摘要

•New “Anytime” Framework for Automatic Algorithm Selection.•Application of the Anytime Automatic Algorithm Selection Framework to Knapsack.•3 Machine Learning Models proposed for the Problem.•Knapsack Instances, Features and Solvers Behavior publicly available.

论文关键词：Knapsack,Algorithm selection problem,Machine learning techniques,Anytime behaviour approach

论文评审过程：Received 4 February 2020, Revised 29 May 2020, Accepted 30 May 2020, Available online 13 June 2020, Version of Record 20 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113613