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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.
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on (Volume:4 )
Date of Conference: 26-29 Aug. 2004