A multi-operator genetic algorithm for the generalized minimum spanning tree problem

作者：

Highlights：

• We propose a multi-operator genetic algorithm for the generalized MST problem.

• Two operators are used for the crossover and five for the mutation.

• A synergic effect emerges from the multi-operator approach.

• An average error of 0.01% was achieved for the 101 most challenging instances.

摘要

•We propose a multi-operator genetic algorithm for the generalized MST problem.•Two operators are used for the crossover and five for the mutation.•A synergic effect emerges from the multi-operator approach.•An average error of 0.01% was achieved for the 101 most challenging instances.

论文关键词：Generalized minimum spanning tree,Genetic algorithms,Multi-operator,Meta-heuristics

论文评审过程：Received 18 January 2015, Revised 11 December 2015, Accepted 13 December 2015, Available online 21 December 2015, Version of Record 6 January 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.12.014