Abstract
This paper introduces a faster and more efficient algorithm for solving a two-dimension packing problem. This common optimization problem takes a set of geometrical objects and tries to find the best form of packing them in a space with specific characteristics, called container. The visualization of nanoscale electromagnetic fields was the inspiration for this new algorithm, using the electromagnetic field between the previously placed objects, this paper explains how to determine the best positions for to place the remaining ones. Two gravitational phenomena are also simulated to achieve better results: shaken and gravity. They help to compact the objects to reduce the occupied space. This paper shows the executions of the packing algorithm for four types of containers: rectangles, squares, triangles, and circles.
Similar content being viewed by others
References
Addis, B., Locatelli, M., & Schoen, F. (2008). Disk packing in a square: A new global optimization approach. Informs Journal of Computing, 20(4), 516–524.
Al-Mudahka, I., Hifi, M., & M’Hallah, R. (2011). Packing circles in the smallest circle: An adaptive hybrid algorithm. Journal of the Operational Research Society, 62, 1917–1930.
Baltaciolu, E., Moore, J., & Hill, R, Jr. (2006). The distributor’s three-dimensional pallet-packing problem: A human intelligence-based heuristic approach. International Journal of Operational Research, 1(3), 249–266. https://doi.org/10.1504/IJOR.2006.009300.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.
Brooke, J., Bitko, D., Rosenbaum, T. F., & Aeppli, G. (1999). Quantum annealing of a disordered magnet. Management Science, 284(5415), 779–781.
Castillo, I., Kampas, F. J., & Pintr, J. D. (2008). Solving circle packing problems by global optimization: Numerical results and industrial applications. European Journal of Operational Research, 191(3), 786–802.
Dell’Amico, M., Dza, J. C. D., & Lori, M. (2012). The bin packing problem with precedence constraints. Operations Research, 60(6), 1491–1504.
Dokeroglu, T., & Cosar, A. (2014). Optimization of one-dimensional bin packing problem with island parallel grouping genetic algorithms. Computers and Industrial Engineering, 75, 176–186.
Eberhart, R., & Kennedy, J. (1995). A new optimizer using particle swarm theory. In Proceedings of the sixth international symposium on micro machine and human science, 1995. MHS ’95 (pp. 39–43).
George, J. A., George, J. M., & Lamar, B. W. (1995). Packing different-sized circles into a rectangular container. European Journal of Operational Research, 84(3), 693–712.
Hatamlou, A. (2013). Black hole: A new heuristic optimization approach for data clustering. Information Sciences, 222, 175–184.
Haus, J. W. (2016). Introduction to nanophotonics. In J. W. Haus (Ed.), Fundamentals and applications of nanophotonics (pp. 1–11). Sawston: Woodhead Publishing.
Holland, J. H. (1992). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control and artificial intelligence. Cambridge, MA: MIT Press.
Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39(3), 459–471.
Litvinchev, I., & Ozuna, E. (2014). Approximate packing circles in a rectangular container: Valid inequalities and nesting. Journal of Applied Research and Technology, 12(4), 716–723. https://doi.org/10.1016/S1665-6423(14)70088-4.
Martinez-Rios, F. (2017). A new hybridized algorithm based on population-based simulated annealing with an experimental study of phase transition in 3-SAT. Procedia Computer Science, 116, 427–434.
Martinez-Rios, F., & Marmolejo-Saucedo, J. A. (2018). Packing instances. http://www.packingproblem.com.
Huang, W. Q., Li, Y., Akeb, H., & Li, C. M. (2005). Greedy algorithms for packing unequal circles into a rectangular container. Journal of the Operational Research Society, 56, 539–548. https://doi.org/10.1057/palgrave.jors.2601836.
Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009). GSA: A gravitational search algorithm. Information Sciences, 179(13), 2232–2248.
Sarangan, A. (2016). Quantum mechanics and computation in nanophotonics. In J. W. Haus (Ed.), Fundamentals and applications of nanophotonics (pp. 45–87). Sawston: Woodhead Publishing.
Seiden, S. (2002). On the online bin packing problem. Journal of ACM, 49(5), 640–671.
Socha, K., Knowles, J., & Sampels, M. (2002). A MAX–MIN ant system for the university course timetabling problem (pp. 1–13). Berlin: Springer.
Steuwe, C., Erdelyi, M., Szekeres, G., Csete, M., Baumberg, J. J., Mahajan, S., et al. (2015). Visualizing electromagnetic fields at the nanoscale by single molecule localization. Nano Letters, 15(5), 3217–3223.
Szabó, P. G., Markót, M. C., & Csendes, T. (2005). Global optimization in geometry—Circle packing into the square (pp. 233–265). Boston, MA: Springer.
Yan, G. W., & Hao, Z. J. (2013). A novel optimization algorithm based on atmosphere clouds model. International Journal of Computational Intelligence and Applications, 12(01), 1350002.
Acknowledgements
I am grateful to my wife Roco for her invaluable help for reviewing the styling and writing of this paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Martinez-Rios, F., Murillo-Suarez, A. Packing algorithm inspired by gravitational and electromagnetic effects. Wireless Netw 26, 5631–5644 (2020). https://doi.org/10.1007/s11276-019-02011-9
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-019-02011-9