New approach to solving the clustered shortest-path tree problem based on reducing the search space of evolutionary algorithm
作者：
Highlights：
• Suggest a method for reducing the search space of the evolutionary algorithm (EA) applied to Clustered Shortest-Path Tree Problem (CluSTP) by decomposing the original problem into two sub-problems.
• The solution of the whole CluSTP is represented compactly only by the solution of first sub-problem.
• Propose an EA to solve the first sub-problem and suggests using the exact algorithm to solve the second sub-problem.
• The Experimental results prove that the new method is more efficient than existing methods.
摘要
•Suggest a method for reducing the search space of the evolutionary algorithm (EA) applied to Clustered Shortest-Path Tree Problem (CluSTP) by decomposing the original problem into two sub-problems.•The solution of the whole CluSTP is represented compactly only by the solution of first sub-problem.•Propose an EA to solve the first sub-problem and suggests using the exact algorithm to solve the second sub-problem.•The Experimental results prove that the new method is more efficient than existing methods.
论文关键词：Genetic algorithm,Clustered shortest-path tree problem,Evolutionary algorithms
论文评审过程：Received 21 September 2018, Revised 27 April 2019, Accepted 9 May 2019, Available online 16 May 2019, Version of Record 12 June 2019.
论文官网地址：https://doi.org/10.1016/j.knosys.2019.05.015
