Solving two dimensional non-guillotine cutting problem Using Particle Swarm Optimization

Abstract

One of the solutions for solving cutting stock problem in different industries, such as sheet metal, lumber, glass, paper and textile, is applying ,Particle Swarm Optimization to minimize the waste of rawmaterials. This article is intended to solve two-dimensional cutting problem. In these problems, larger rectangular plates, divided into smaller rectangularsegments, aim to minimizing the number of used plates or the waste of plates by considering demand. In this article PSO is used. To enhance the efficiency of algorithm, and preventing overlap in cutting problem, the CUL algorithm is used. In order to investigate the results of algorithm, new software has been designed. This software has two ways for solving the problem. First, it ends up with optimized cutting pattern considering the number and dimension of segments and, length and width of main plate. Also, there is a possibility to give different width to software, in this case, the software gives the user the optimum cutting pattern and optimum length of main plate in addition to optimum widt