A heuristic particle swarm optimization for cutting stock problem based on cutting pattern

Abstract

A heuristic particle swarm optimization (HPSO) is proposed as a solution to one-dimensional cutting stock problem (1D-CSP), which incorporate genetic operators into particle swarm optimization (PSO). In this paper, a heuristic strategy that is based on the results of analysis of the optimal cutting pattern of particles with successful search processes is described, which process a global optimization problem of the cutting-stock as a sequential optimization problem by multiple stages. During every sequential stage, the best cutting pattern for the current situation is researched and processed. This strategy is repeated until all the required stocks have been generated. The simulation results prove the effectiveness of the proposed methodology. © Springer-Verlag Berlin Heidelberg 2007.