Abstract
The set cover problem is a classical question in combinatorics, computer science and complexity theory. It is one of Karp’s 21 NP-complete problems shown to be NP-complete in 1972. Several algorithms have been proposed to solve this problem, based on genetic algorithms (GA), Particle Swarm Optimizer (PSO) and in recent years algorithms based in behavior algorithms based groups or herds of animals, such as frogs, bats, bees and domestic cats. This work presents the basic features of the algorithm based on the behavior of domestic cats and results to solve the SCP bi-objective, experimental results and opportunities to improve results using adaptive techniques applied to Cat Swarm Optimization. For this purpose we will use instances of SCP OR-Library of Beasley by adding an extra function fitness to transform the Beasly instance to Bi-Objective problem.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Crawford, B., Soto, R., Cuesta, R., Olivares-Suárez, M., Johnson, F., Olguin, E.: Two swarm intelligence algorithms for the set covering problem. In: 2014 9th International Conference on Software Engineering and Applications (ICSOFT-EA), pp. 60–69. IEEE (2014)
Crawford, B., Soto, R., Peña, C., Riquelme-Leiva, M., Torres-Rojas, C., Misra, S., Johnson, F., Paredes, F.: A comparison of three recent nature-inspired metaheuristics for the set covering problem. In: Gervasi, O., Murgante, B., Misra, S., Gavrilova, M.L., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2015. LNCS, vol. 9158, pp. 431–443. Springer, Heidelberg (2015)
Gervasi, O., Murgante, B., Misra, S., Gavrilova, M.L., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O. (eds.): ICCSA 2015. LNCS, vol. 9158. Springer, Heidelberg (2015)
Lopez, J., Lanzarini, L.C., Leguizamón, G.: Optimización multiobjetivo: aplicaciones a problemas del mundo real. Buenos Aires, Argentina, Universidad Nacional de la Plata, pp. 66–90 (2013)
Wikipedia, Problema del conjunto de cobertura – wikipedia, la enciclopedia libre (2014). [Internet; descargado 29-octubre-2015]
Zitzler, E., Thiele, L.: Multiobjective optimization using evolutionary algorithms–a comparative case study. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) Parallel Problem Solving from Nature—PPSN V. LNCS, vol. 1498, pp. 292–301. Springer, Heidelberg (1998)
Wikipedia, Pareto efficiency – wikipedia, the free encyclopedia (2015). Accessed 29 Oct 2015
Knowles, J., Corne, D.: The pareto archived evolution strategy: a new baseline algorithm for pareto multiobjective optimisation. In: Proceedings of the 1999 Congress on Evolutionary Computation, 1999, CEC 99, vol. 1, IEEE (1999)
Caprara, A., Toth, P., Fischetti, M.: Algorithms for the set covering problem. Ann. Oper. Res. 98(1–4), 353–371 (2000)
Crawford, B., Soto, R., Berrios, N., Johnson, F., Paredes, F.: Binary cat swarm optimization for the set covering problem pp. 1–4 (2015)
Chu, S.-C., Tsai, P.-W.: Computational intelligence based on the behavior of cats. Int. J. Innovative Comput. Inf. Control 3(1), 163–173 (2007)
Beasley, J.E.: A lagrangian heuristic for set-covering problems. Nav. Res. Logistics (NRL) 37(1), 151–164 (1990)
Pradhan, P.M., Panda, G.: Solving multiobjective problems using cat swarm optimization. Expert Syst. Appl. 39(3), 2956–2964 (2012)
Chu, S.-C., Tsai, P., Pan, J.-S.: Cat swarm optimization. In: Yang, Q., Webb, G. (eds.) PRICAI 2006. LNCS (LNAI), vol. 4099, pp. 854–858. Springer, Heidelberg (2006)
Panda, G., Pradhan, P.M., Majhi, B.: IIR system identification using cat swarm optimization. Expert Syst. Appl. 38(10), 12671–12683 (2011)
Lust, T., Tuyttens, D.: Two-phase pareto local search to solve the biobjective set covering problem. In: 2013 Conference on Technologies and Applications of Artificial Intelligence (TAAI), pp. 397–402. IEEE (2013)
Durillo, J.J., Nebro, A.J.: jmetal: A java framework for multi-objective optimization. Ad. Eng. Softw. 42(10), 760–771 (2011)
Wikipedia, Optimización multiobjetivo – wikipedia, la enciclopedia libre (2013). [Internet; descargado 29-octubre-2015]
Friedrich, T., He, J., Hebbinghaus, N., Neumann, F., Witt, C.: Approximating covering problems by randomized search heuristics using multi-objective models*. Evol. Comput. 18(4), 617–633 (2010)
Vazirani, V.V.: Approximation Algorithms. Springer Science & Business Media, New York (2013)
Bouzidi, A., Riffi, M.E.: Cat swarm optimization to solve flow shop scheduling problem. J. Theor. Appl. Inf. Technol. 72(2) (2015)
Hadi, I., Sabah, M.: Improvement cat swarm optimization for efficient motion estimation. Int. J. Hybrid Inf. Technol. 8(1), 279–294 (2015)
Musliu, N.: Local search algorithm for unicost set covering problem. In: Ali, M., Dapoigny, R. (eds.) IEA/AIE 2006. LNCS (LNAI), vol. 4031, pp. 302–311. Springer, Heidelberg (2006)
Zhang, L.-B., Zhou, C.-G., Liu, X., Ma, Z., Ma, M., Liang, Y.: Solving multi objective optimization problems using particle swarm optimization. In: Proceedings of IEEE congress on evolutionary computation, pp. 2400–2405 (2003)
Crawford, B., Soto, R., Aballay Leiva, F., Johnson, F., Paredes, F.: The set covering problem solved by the binary teaching-learning-based optimization algorithm. In: 2015 10th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–4. IEEE (2015)
Crawford, B., Soto, R., Peña, C., Riquelme-Leiva, M., Torres-Rojas, C., Johnson, F., Paredes, F.: Binarization methods for shuffled frog leaping algorithms that solve set covering problems. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Prokopova, Z., Silhavy, P. (eds.) Software Engineering in Intelligent Systems. AISC, vol. 349, pp. 317–326. Springer, Heidelberg (2013)
Crawford, B., Soto, R., Aballay, F., Misra, S., Johnson, F., Paredes, F.: A teaching-learning-based optimization algorithm for solving set covering problems. In: Gervasi, O., Murgante, B., Misra, S., Gavrilova, M.L., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2015. LNCS, vol. 9158, pp. 421–430. Springer, Heidelberg (2015)
Crawford, B., Soto, R., Torres-Rojas, C., Peña, C., Riquelme-Leiva, M., Misra, S., Johnson, F., Paredes, F.: A binary fruit fly optimization algorithm to solve the set covering problem. In: Gervasi, O., Murgante, B., Misra, S., Gavrilova, M.L., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2015. LNCS, vol. 9158, pp. 411–420. Springer, Heidelberg (2015)
Cuesta, R., Crawford, B., Soto, R., Paredes, F.: An artificial bee colony algorithm for the set covering problem. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Silhavy, P., Prokopova, Z. (eds.) Modern Trends and Techniques in Computer Science. AISC, vol. 285, pp. 53–63. Springer, Heidelberg (2014)
Acknowledgements
The author Broderick Crawford is supported by grant CONICYT/FONDECYT/REGULAR/1140897 and Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1160455.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Crawford, B., Soto, R., Caballero, H., Olguín, E., Misra, S. (2016). Solving Biobjective Set Covering Problem Using Binary Cat Swarm Optimization Algorithm. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9786. Springer, Cham. https://doi.org/10.1007/978-3-319-42085-1_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-42085-1_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42084-4
Online ISBN: 978-3-319-42085-1
eBook Packages: Computer ScienceComputer Science (R0)