Abstract
The Set Covering Problem (SCP) is a classic problem in combinatorial optimization. SCP has many applications in engineering, including problems involving routing, scheduling, stock cutting, electoral redistricting and others important real life situations. Because of its importance, SCP has attracted attention of many researchers. However, SCP instances are known as complex and generally NP-hard problems. Due to the combinatorial nature of this problem, during the last decades, several metaheuristics have been applied to obtain efficient solutions. This paper presents a metaheuristics comparison for the SCP. Three recent nature-inspired metaheuristics are considered: Shuffled Frog Leaping, Firefly and Fruit Fly algorithms. The results show that they can obtainn optimal or close to optimal solutions at low computational cost.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Foster, B.A., Ryan, D.M.: An integer programming approach to the vehicle scheduling problem. Operational Research Quarterly 27, 367–384 (1976)
Beasley, J., Chu, P.: A genetic algorithm for the set covering problem. European Journal of Operational Research 94(2), 392–404 (1996)
Boros, E., Hammer, P.L., Ibaraki, T., Kogan, A.: Logical analysis of numerical data. Math. Program. 79, 163–190 (1997)
Caprara, A., Fischetti, M., Toth, P.: A heuristic method for the set covering problem. Operations Research 47(5), 730–743 (1999)
Constantine, T., Ralph, S., Charles, R., Lawrence, B.: The location of emergency service facilities. Operations Research 19, 1363–1373 (1971)
Crawford, B., Soto, R., Cuesta, R., Paredes, F.: Application of the Artificial Bee Colony Algorithm for Solving the Set Covering Problem. The Scientific World Journal 2014, 8 (2014)
Crawford, B., Soto, R., Olivares-Suárez, M., Paredes, F.: A binary firefly 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. 65–73. Springer, Heidelberg (2014)
Crawford, B., Soto, R., Olivares-Suárez, M., Paredes, F.: Using the firefly optimization method to solve the weighted set covering problem. In: Stephanidis, C. (ed.) HCI 2014, Part I. CCIS, vol. 434, pp. 509–514. Springer, Heidelberg (2014)
Eusuff, M., Lansey, K.: Optimization of water distribution network design usingthe shuffled frog leaping algorithm. Journal of Water Resource Plan Management 129, 210–225 (2003)
Eusuff, M., Lansey, K., Pasha, F.: Shuffled frog-leaping algorithm: a memeticmeta-heuristic for discrete optimization. Engineering Optimization 38, 129–154 (2006)
Vasko, F.J., Wolf, F.E., Stott, K.L.: A set covering approach to metallurgical grade assignment. European Journal of Operational Research 38(1), 27–34 (1989)
Fisher, M.L., Rosenwein, M.B.: An interactive optimization system for bulk-cargo ship scheduling. Naval Research Logistics 36, 27–42 (1989)
Lin, S.-M.: Analysis of service satisfaction in web auction logistics service using a combination of fruit fly optimization algorithm and general regression neural network. Neural Computing and Applications 22(3–4), 783–791 (2013)
Liong, S., Atiquzzaman, M.: Optimal design of water distribution network usingshuffled complex evolution. Journal of Instrumentation Engineering 44, 93–107 (2004)
Smith, B.M.: Impacs a bus crew scheduling system using integer programming. Mathematical Programming 42(1–3), 181–187 (1998)
Pan, W.-T.: A new fruit fly optimization algorithm: Taking the financial distress model as an example. Knowl.-Based Syst. 26, 69–74 (2012)
Valenzuela, C., Crawford, B., Soto, R., Monfroy, E., Paredes, F.: A 2-level metaheuristic for the set covering problem. International Journal of Computers Communications and Control 7(2), 377–387 (2012)
Wang, L., Zheng, X., Wang, S.: A novel binary fruit fly optimization algorithm for solving the multidimensional knapsack problem. Knowl.-Based Syst. 48, 17–23 (2013)
Yang, X.-S.: Nature-inspired metaheuristic algorithms. Luniver Press (2010)
Ze Li, H., Guo, S., Jie Li, C., Qi Sun, J.: A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm. Knowledge-Based Systems 37, 378–387 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Crawford, B. et al. (2015). A Comparison of Three Recent Nature-Inspired Metaheuristics for the Set Covering Problem. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9158. Springer, Cham. https://doi.org/10.1007/978-3-319-21410-8_34
Download citation
DOI: https://doi.org/10.1007/978-3-319-21410-8_34
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21409-2
Online ISBN: 978-3-319-21410-8
eBook Packages: Computer ScienceComputer Science (R0)