An improved Shuffled Frog-leaping Algorithm to optimize component pick-and-place sequencing optimization problem

作者：

Highlights：

• An improved Shuffled Frog-leaping Algorithm (SFLA) was presented.

• All frogs take part in memetic evolution and have the self-variation behavior.

• Three-way ANOVA was used for better parameter setting of the improved SFLA.

• The improved SFLA outperforms SFLA and GA in terms of convergence accuracy.

• The method to solve the discrete optimal issue with the new SFLA was introduced.

摘要

•An improved Shuffled Frog-leaping Algorithm (SFLA) was presented.•All frogs take part in memetic evolution and have the self-variation behavior.•Three-way ANOVA was used for better parameter setting of the improved SFLA.•The improved SFLA outperforms SFLA and GA in terms of convergence accuracy.•The method to solve the discrete optimal issue with the new SFLA was introduced.

论文关键词：Combinatorial optimization,Component placement sequence optimization,Shuffled Frog-leaping Algorithm,A Shuffled Frog-leaping Algorithm with variation behavior

论文评审过程：Available online 9 May 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.04.038