A biased random key genetic algorithm for open dimension nesting problems using no-fit raster

作者：

Highlights：

• Irregular 2D cutting problems with one or two open dimensions are tackled.

• The no-fit raster concept is extended to deal with free form items.

• A BRKGA combined with bottom-left heuristics is proposed to solve the problems.

• It outperforms recent methods from the literature on different set of instances.

• Instances with items as circles, convex and non-convex polygons are solved.

摘要

•Irregular 2D cutting problems with one or two open dimensions are tackled.•The no-fit raster concept is extended to deal with free form items.•A BRKGA combined with bottom-left heuristics is proposed to solve the problems.•It outperforms recent methods from the literature on different set of instances.•Instances with items as circles, convex and non-convex polygons are solved.

论文关键词：Nesting problems,Open dimension problems,No-fit raster,Bottom-left,Biased random key genetic algorithm

论文评审过程：Received 11 March 2016, Revised 17 February 2017, Accepted 25 March 2017, Available online 29 March 2017, Version of Record 5 April 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.03.059