A novel grouping particle swarm optimization approach for 2D irregular cutting stock problem

作者：Xu, Yanxin^*

来源：International Journal of Control and Automation, 2016, 9(8): 369-380.

DOI：10.14257/ijca.2016.9.8.35

• Building industry
• Conventional methods
• Cutting stock problem
• GPSO
• Grouping problem
• Particle position
• Particle swarm optimization approaches

The Cutting stock problem is an important problem that arises in a variety of industrial applications. The problem includes a grouping phase (the grouping problem). This research adopts a novel grouping particle swarm optimization approach for grouping problem. In this article, new particle position and velocity updating equations are developed according to the structure of grouping problem for cutting stock problem. The approach works with groups of items instead of items exclusively, compared with conventional method for cutting stock problem. The proposed approach is tested on a set of real instances from the ship building industry with very good results. Moreover, the efficacy and efficiency of the proposed approach are indicated on a set of randomly generated instances.

• 出版日期2016
• 单位上海交通大学