Ant inspired Monte Carlo algorithm for minimum feedback arc set

作者：

Highlights：

• The algorithm is on average 20% more efficient (faster).

• The algorithm has 511% (158%) (mean, median) faster convergence.

• Probability bound is calculated.

• The algorithm can potentially have many applications.

摘要

•The algorithm is on average 20% more efficient (faster).•The algorithm has 511% (158%) (mean, median) faster convergence.•Probability bound is calculated.•The algorithm can potentially have many applications.

论文关键词：Minimum feedback arc set,Monte carlo,Randomization,Ant colony optimization,Arbitrary probability

论文评审过程：Received 16 July 2018, Revised 3 November 2018, Accepted 13 December 2018, Available online 31 December 2018, Version of Record 5 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.021