Abstract
In this paper we present Artificial Fish Swarm Algorithm (AFSA) applying to a two-dimensional non-guillotine cutting stock problem. Meanwhile, we use a converting approach which is similar to the Bottom Left (BL) algorithm to map the cutting pattern to the actual layout. Finally, we implement Artificial Fish Swarm Algorithm on several test problems. The simulated results show that the performance of Artificial Fish Swarm Algorithm is better than that of Particle Swarm Optimization Algorithm.
Supported by the National Natural Science Funds of China under Grant No. 61163034.
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Bao, L., Jiang, Jq., Song, C., Zhao, L., Gao, J. (2013). Artificial Fish Swarm Algorithm for Two-Dimensional Non-Guillotine Cutting Stock Problem. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_66
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DOI: https://doi.org/10.1007/978-3-642-39068-5_66
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