Abstract
The Set Covering Problem (SCP) consists in finding a set of solutions that allow to cover a set of necessities with the minor possible cost. There are many applications of this problem such as rolling production lines or installation of certain services like hospitals. SCP has been solved before with different algorithms like genetic algorithm, cultural algorithm or firefly algorithm among others. The objective of this paper is to show the performance of an Artificial Fish Swarm Algorithm (AFSA) in order to solve SCP. This algorithm, simulates the behavior of a fish shoal inside water and it uses a population of points in space to represent the position of a fish in the shoal. Here we show a study of its simplified version of AFSA in a binary domain with its modifications applied to SCP. This method was tested on SCP benchmark instances from OR-Library website.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman & Co., New York (1990)
Crawford, B., Soto, R., Aguilar, R.C., Paredes, F.: A new artificial bee colony algorithm for set covering problems. Electr. Eng. Inf. Technol. 63, 31 (2014)
Crawford, B., Soto, R., Aguilar, R.C., Paredes, F.: Application of the artificial bee colony algorithm for solving the set covering problem. Sci. World J. 2014, 1–8 (2014)
Crawford, B., Soto, R., Monfroy, E.: Cultural algorithms for the set covering problem. In: Tan, Y., Shi, Y., Mo, H. (eds.) ICSI 2013, Part II. LNCS, vol. 7929, pp. 27–34. Springer, Heidelberg (2013)
Crawford, B., Soto, R., Monfroy, E., Palma, W., Castro, C., Paredes, F.: Parameter tuning of a choice-function based hyperheuristic using Particle Swarm Optimization. Expert Syst. Appl. 40(5), 1690–1695 (2013)
Crawford, B., Soto, R., Monfroy, E., Paredes, F., Palma, W.: A hybrid Ant algorithm for the set covering problem (2014)
Crawford, B., Soto, R., Olivares-Suárez, M., Paredes, F.: A binary firefly algorithm for the set covering problem. Modern Trends Tech. Comput. Sci. 285, 65–73 (2014)
Crawford, B., Soto, R., Riquelme-Leiva, M., Peña, C., Torres-Rojas, C., Johnson, F., Paredes, F.: Modified binary firefly algorithms with different transfer functions for solving set covering problems. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Prokopova, Z., Silhavy, P. (eds.) CSOC 2015. AISC, vol. 349, pp. 307–315. Springer, Cham (2015)
Crawford, B., Soto, R., Peña, C., Palma, W., Johnson, F., Paredes, F.: Solving the set covering problem with a shuffled frog leaping algorithm. In: Nguyen, N.T., Trawiński, B., Kosala, R. (eds.) ACIIDS 2015. LNCS, vol. 9012, pp. 41–50. Springer, Heidelberg (2015)
Michalewicz, Z.: Genetic Algorithms \(+\) Data Structures \(=\) Evolution Programs, 3rd edn. Springer, Heidelberg (1996)
Azad, M.A.K., Rocha, A.M.A.C., Fernandes, E.M.G.P.: Solving multidimensional 0–1 knapsack problem with an artificial fish swarm algorithm. In: Murgante, B., Gervasi, O., Misra, S., Nedjah, N., Rocha, A.M.A.C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2012, Part III. LNCS, vol. 7335, pp. 72–86. Springer, Heidelberg (2012)
Azad, M.A.K., Rocha, A.M.A., Fernandes, E.M.: Improved binary artificial fish swarm algorithm for the 0–1 multidimensional knapsack problems. Swarm Evol. Comput. 14, 66–75 (2014)
Azad, M.A.K., Rocha, A.M.A., Fernandes, E.M.: Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm. J. Math. Model. Algorithms Oper. Res. 14, 313–330 (2015)
Balas, E., Ho, A.: Set covering algorithms using cutting planes, heuristics, and subgradient optimization: a computational study. In: Padberg, M.W. (ed.) Combinatorial Optimization, pp. 37–60. Springer, Heidelberg (1980)
Beasley, J.E.: An algorithm for set covering problem. Eur. J. Oper. Res. 31(1), 85–93 (1987)
Beasley, J.E.: A Lagrangian heuristic for set-covering problems. Naval Res. Logist. (NRL) 37(1), 151–164 (1990)
Acknowledgements
Broderick Crawford is supported by Grant CONICYT/FONDECYT/REGULAR/1140897. Ricardo Soto is supported by Grant CONICYT/FONDECYT/REGULAR/1160455. Sebastián Mansilla Villablanca, Álvaro Gómez, Adrián Jaramillo and Juan Salas are supported by Postgraduate Grant Pontificia Universidad Católica de Valparaíso 2016 (INF-PUCV 2016).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
A Appendix
A Appendix
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Crawford, B. et al. (2016). An Artificial Fish Swarm Optimization Algorithm to Solve Set Covering Problem. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_76
Download citation
DOI: https://doi.org/10.1007/978-3-319-42007-3_76
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-42006-6
Online ISBN: 978-3-319-42007-3
eBook Packages: Computer ScienceComputer Science (R0)