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

Abstract

One of the solutions for solving cutting stock problem in differentindustries, such as sheet metal, lumber, glass, paper and textile, isapplying ,Particle Swarm Optimization to minimize the waste ofrawmaterials. This article is intended to solve two-dimensional cuttingproblem. In these problems, larger rectangular plates, divided intosmaller rectangularsegments, aim to minimizing the number of usedplates or the waste of plates by considering demand. In this articlePSO is used. To enhance the efficiency of algorithm, and preventingoverlap in cutting problem, the CUL algorithm is used. In order toinvestigate the results of algorithm, new software has been designed.This software has two ways for solving the problem. First, it ends upwith optimized cutting pattern considering the number and dimensionof segments and, length and width of main plate. Also, there is apossibility to give different width to software, in this case, thesoftware gives the user the optimum cutting pattern and optimumlength of main plate in addition to optimum width

Keywords

• optimization
• meta-heuristic algorithms
• discrete particle swarm optimization (dpso)
• cul algorithm
• twodimensional cutting problem