Abstract
In this paper we introduce an evolutionary hyperheuristic approach to solve difficult strip packing problems. We have designed a genetic based hyperheuristic using the most recently proposed low-level heuristics in the literature. Two versions for tuning parameters have also been evaluated. The results obtained are very encouraging showing that our approach outperforms the single heuristics and others well-known techniques.
Partially Supported by the Fondecyt Project 1060377.
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References
Alvarez, R., Parreño, F., Tamarit, J.M.: Reactive grasp for the strip packing problem. In: Proceedings of the 6th Metaheuristics International Conference, vol. 1 (2005)
Baker, B.S., Coffman, E.G., Rivest, R.L.: Orthogonal packings in two dimensions. SIAM Journal on Computing 9, 846–855 (1980)
Bortfeldt, A.: A genetic algorithm for the two-dimensional strip packing problem with rectangular pieces. European Journal of Operational Research 172, 814–837 (2006)
Bortfeldt, A., Gehring, H.: New large benchmark instances for the two-dimensional strip packing problem with rectangular pieces. In: IEEE Proceedings of the 39th Annual Hawaii International Conference on System Sciences, vol. 2, pp. 30–32 (2006)
Burke, E., Kendall, G., Newall, J., Hart, E., Ross, P., Schulenburg, S.: Hyper-heuristics: an emerging direction in modern search technology. Handbook of Metaheuristics 16, 457–474 (2003)
Burke, E., Kendall, G., Whitwell, G.: A new placement heuristic for the ortoghonal stock-cutting problem. Operations Research 52, 655–671 (2004)
Chazelle, B.: The bottom-left bin packing heuristic: an efficient implementation. IEEE Transactions on Computers 32, 697–707 (1983)
Cowling, P., Kendall, G., Han, L.: An investigation of a hyperheuristic genetic algorithm applied to a trainer scheduling problem. In: Proceedings of Congress on Evolutionary Computation, pp. 1185–1190 (2002)
Han, L., Kendall, G.: Guided operators for a hyper-heuristic genetic algorithm. In: Gedeon, T.D., Fung, L.C.C. (eds.) AI 2003. LNCS (LNAI), vol. 2903, pp. 807–820. Springer, Heidelberg (2003)
Hopper, E.: Two-Dimensional Packing Utilising Evolutionary Algorithms and other Meta-Heuristic Methods. PhD. Thesis Cardiff University, UK (2000)
Hopper, E., Turton, B.C.H.: An empirical investigation on metaheuristic and heuristic algorithms for a 2d packing problem. European Journal of Operational Research 128, 34–57 (2001)
Iori, M., Martello, S., Monaci, M.: Metaheuristic algorithms for the strip packing problem, pp. 159–179. Kluwer Academic Publishers, Dordrecht (2003)
Lesh, N., Marks, J., Mc Mahon, A., Mitzenmacher, M.: Exhaustive approaches to 2d rectangular perfect packings. Information Processing Letters 90, 7–14 (2004)
Lesh, N., Mitzenmacher, M.: Bubble search: A simple heuristic for improving priority-based greedy algorithms. Information Processing Letters 97, 161–169 (2006)
Martello, S., Monaci, M., Vigo, D.: An exact approach to the strip-packing problem. INFORMS Journal of Computing 15, 310–319 (2003)
Mumford-Valenzuela, C., Vick, J., Wang, P.Y.: Heuristics for large strip packing problems with guillotine patterns: An empirical study, pp. 501–522. Kluwer Academic Publishers, Dordrecht (2004)
Nannen, V., Eiben, A.E.: Relevance estimation and value calibration of evolutionary algorithm parameters. In: International Joint Conference on Artificial Intelligence, pp. 975–980 (2007)
Soke, A., Bingul, Z.: Hybrid genetic algorithm and simulated annealing for two-dimensional non-guillotine rectangular packing problems. Engineering Applications of Artificial Intelligence 19, 557–567 (2006)
Zhang, D., Kang, Y., Deng, A.: A new heuristic recursive algorithm for the strip rectangular packing problem. Computers and Operations Research 33, 2209–2217 (2006)
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Garrido, P., Riff, MC. (2007). An Evolutionary Hyperheuristic to Solve Strip-Packing Problems. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_42
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DOI: https://doi.org/10.1007/978-3-540-77226-2_42
Publisher Name: Springer, Berlin, Heidelberg
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