An effective and efficient fruit fly optimization algorithm with level probability policy and its applications

作者：

Highlights：

• A level probability policy and new mutation parameter are used for proposed FOA.

• Results of 29 test functions show LP–FOA outperforms the existing FOAs, DE and PSO.

• A delicate LP–FOA based coding is used to solve joint replenishment problem (JRP).

• LP–FOA is better than the current best intelligent algorithm for JRPs.

摘要

•A level probability policy and new mutation parameter are used for proposed FOA.•Results of 29 test functions show LP–FOA outperforms the existing FOAs, DE and PSO.•A delicate LP–FOA based coding is used to solve joint replenishment problem (JRP).•LP–FOA is better than the current best intelligent algorithm for JRPs.

论文关键词：Fruit fly optimization algorithm,Level probability,Continuous function problem,Joint replenishment problems

论文评审过程：Received 5 May 2015, Revised 3 January 2016, Accepted 4 January 2016, Available online 12 January 2016, Version of Record 20 February 2016.

论文官网地址：https://doi.org/10.1016/j.knosys.2016.01.006