A hybrid algorithm based on PSO and genetic operation and its applications for cutting stock problem

摘要

A hybrid algorithm based on particle swarm optimization (PSO) and genetic operations is presented and applied to the constrained two-dimensional non-guillotine cutting stock problem. A converting approach similar to the bottom left (BL) algorithm is also used to map the cutting pattern to the actual layout. Simulations show that the proposed algorithm reduces the probability of trapping in the local optimum and is effective for dealing with the cutting stock problem.