Automated design of search algorithms: Learning on algorithmic components

作者：

Highlights：

• A framework for automated design of local search algorithms.

• Various local search algorithms are modelled within the framework.

• The vehicle routing problems are used as the domain problem.

• Performance of elementary algorithmic components is analysed.

• Two learning models based on reinforcement learning and Markov chain are compared.

摘要

•A framework for automated design of local search algorithms.•Various local search algorithms are modelled within the framework.•The vehicle routing problems are used as the domain problem.•Performance of elementary algorithmic components is analysed.•Two learning models based on reinforcement learning and Markov chain are compared.

论文关键词：Automated algorithm design,Search algorithms,Reinforcement learning,Markov chain

论文评审过程：Received 15 September 2020, Revised 13 May 2021, Accepted 24 June 2021, Available online 22 July 2021, Version of Record 31 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115493