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2D Irregular

Note

The entries below represent the original dataset files from each respective publication. Many of these datasets have been converted to a common format by Jeroen Gardeyn and are publicly available at https://github.com/Oscar-Oliveira/OR-Datasets

  • albano

    • Data set from the textile industry, scanned by E. Hopper from sample layout in Albano A. and Sappupo G., 1980, “Optimal Allocation of two-dimensional irregular shapes using heuristic search methods”, IEEE Transactions on Systems, Man and Cybernetics, SMC-10, 242-248.

  • blaz

    • Artificially created data set, based in Blazewicz J., Hawryluk P. and Walkowiak R., 1993, “Using a tabu search approach for solving the two-dimensional irregular cutting problem”, Annals of Operations Research 41, 313-327, coordinates stated in Oliveira J. F., Gomes A. M. and Ferreira S., 2000, “A new constructive algorithm for nesting problems”, OR Spectrum 22 (2), 263-284.
    • Sometimes referred to as SHAPES2

  • dagli

    • Data set from the textile industry, scanned by E. Hopper from sample layout in Ratanapan K. and Dagli C. H., 1997, “An object-based evolutionary algorithm for solving irregular nesting problems”, In: Proceedings for Artificial Neural Networks in Engineering Conference (ANNIE’97), vol. 7, ASME Press, New York, pp. 383-388.

  • dighe

    • Jigsaw problems (with known optimum), constructed by E. Hopper according to a sample layout in Dighe R. and Jakiela M. J., 1996, “Solving Pattern Nesting Problems with Genetic Algorithms Employing Task Decomposition and Contact Detection”, Evolutionary Computation 3, 239-266.

  • fu

    • Artificially created data set, scanned by E. Hopper from sample layout in Fujita K., Akagji, S. and Kirokawa, N., 1993, “Hybrid approach for optimal nesting using a genetic algorithm and a local minimisation algorithm”, Proceedings of the 19th Annual ASME Design Automation Conference, Part 1 (of 2), Albuquerque, NM, USA, vol. 65, part 1, pp. 477-484.

  • gardeyn

    • Gardeyn, J., Berghe, G. V., & Wauters, T. (2025). An open-source heuristic to reboot 2D nesting research. arXiv preprint https://doi.org/10.48550/arXiv.2509.13329.
    • Ten challenging 2D irregular strip packing instances derived from various real-world applications. Both 90-degree and continuous rotation versions are provided.

  • guillotine

    • Irregular Guillotine Bin Packing
    • [No further description or reference]

  • han

    • Artificially created data set, scanned by E. Hopper from sample layout in Han G. C. and Na S. J., 1996, “Two-stage approach for nesting in two-dimensional cutting problems using neural network and simulated annealing”, In: Proceedings of the Institute of Mechanical Engineers, Part B, Journal of Engineering Manufacture 210, B6, pp. 509-519.

  • jakobs

    • Artificially created data set, constructed by E. Hopper from sample layout in Jakobs S., 1996, “On genetic algorithms for the packing of polygons”, European Journal of Operations Research 88, 165-181.

  • mao

    • Data set from the textile industry, scanned by E. Hopper from sample layout in Bounsaythip C. and Maouche S., 1997, “Irregular shape nesting and placing with evolutionary approach”, In: Proceedings of the IEEE International Conference On Systems, Man and Cybernetics, vol. 4, pp. 3425-3430.

  • marques

    • Data set from the textile industry, scanned by E. Hopper from sample layout in Marques V. M. M., Bispo C. F .G. and Sentieiro J. J. S., 1991, “A system for the compaction of two-dimensional irregular shapes based on simulated annealing”, Proceedings of the 1991 International Conference on Industrial Electronics, Control and Instrumentation – IECON ’91, Kobe, Japan, Oct. 1991, pp. 1911-1916.

  • poly

    • Artificially created data set, coordinates stated in Hopper, Eva, “Two-dimensional Packing utilising Evolutionary Algorithms and other Meta-Heuristic Methods”, PhD Thesis, Cardiff University, School of Engineering, 2000.

  • shapes

    • Artificially created data set, coordinates stated in Oliveira J. F., Gomes A. M. and Ferreira S., 2000, “A new constructive algorithm for nesting problems”, OR Spectrum 22 (2), 263-284.

  • shirts

    • Data set from the textile industry, instance initially used in Dowsland K. A., Dowsland W. B. and Bennell J. A., 1998, “Jostling for position: local improvement for irregular cutting patterns”, Journal of the Operational Research Society 49, 647-658, coordinates stated in Oliveira J. F., Gomes A. M. and Ferreira S., 2000, “A new constructive algorithm for nesting problems”, OR Spectrum 22 (2), 263-284.

  • swim

    • Data set from the textile industry, instance initially used in Dowsland K. A., Dowsland W. B. and Bennell J. A., 1998, “Jostling for position: local improvement for irregular cutting patterns”, Journal of the Operational Research Society 49, 647-658, coordinates stated in Oliveira J. F., Gomes A. M. and Ferreira S., 2000, “A new constructive algorithm for nesting problems”, OR Spectrum 22 (2), 263-284.

  • terashima1

    • 540 Irregular test instances artificially created data set with convex polygons.
    • Procedure described by Terashima-Marín, H., Ross, P., Farías-Zárate, C. J., López-Camacho, E., and Valenzuela-Rendón, M. Generalized hyper-heuristics for solving 2D regular and irregular packing problems. Annals of Operations Research 179 (2010), 369-392

  • terashima2

    • 480 Irregular test instances artificially created data set with convex and non-convex polygons.
    • Procedure described by López-Camacho, E. An Evolutionary Framework for Producing Hyper-heuristics for Solving the 2D Irregular Bin Packing Problem PhD Dissertation. Tecnológico de Monterrey, 2012.

  • three

    • Artificially created data set, based in Alvarez-Valdes, R., A. Martinez, and J. Tamarit, 2013 “A branch & bound algorithm for cutting and packing irregularly shaped pieces”, International Journal of Production Economics 145 (2), 463 – 477.

  • trousers

    • Data set from the textile industry, coordinates stated in Oliveira J. F., Gomes A. M. and Ferreira S., 2000, “A new constructive algorithm for nesting problems”, OR Spectrum 22 (2), 263-284.