Abstract
The set covering problem is a fundamental model which comprises a wide range of important applications such as crew scheduling problems that need to cover a set of trips. It is one of the most common issues in the facility location problem, which requires further investigations, particularly in emergency and service facilities. As such, the objective of this study is to propose a new coefficient-based heuristic algorithm for the set covering problems. This paper has accordingly presented the algorithm that evaluates the qualification of subsets by directly applying a fitness function. This fitness function is formulated based on sets and subsets coefficients in a way that the subsets of selected sets have the lowest probability to be selected in the next iteration. The algorithm is not only capable of constructing an answer within polynomial time, but can solve complex set covering problems without conventional restrictions. The performance of this algorithm is evaluated on benchmark instances including a set of reproduced and selected OR-library problems within different sizes. Computational results indicate that the proposed heuristic algorithm produces better solutions, especially in large-scale problems comparing simulated annealing in terms of quality and time.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Wang, K.J., Lestari, Y.D., Tran, V.N.B.: Location selection of high-tech manufacturing firms by a fuzzy analytic network process: a case study of Taiwan high-tech industry. Int. J. Fuzzy Syst. 19(5), 1560–1584 (2017)
Farahani, R.Z., Hekmatfar, M.: Facility Location: Concepts, Models, Algorithms and Case Studies. Springer, Berlin (2009)
Beasley, J.E., Jörnsten, K.: Enhancing an algorithm for set covering problems. Eur. J. Oper. Res. 58(2), 293–300 (1992)
Liu, Z., Xu, H., Liu, P., Li, L., Zhao, X.: Interval-valued intuitionistic uncertain linguistic multi-attribute decision-making method for plant location selection with partitioned hamy mean. Int. J. Fuzzy Syst. 22(6), 1993–2010 (2020)
Solar, M., Parada, V., Urrutia, R.: A parallel genetic algorithm to solve the set-covering problem. Comput. Oper. Res. 29(9), 1221–1235 (2002)
Bahrami, I., Ahari, R.M., Asadpour, M.: A maximal covering facility location model for emergency services within an M (t)/M/m/m queuing system. J. Model. Manag. 16(3), 963–986 (2021)
Li, R., Hu, S., Cai, S., Gao, J., Wang, Y., Yin, M.: NuMWVC: a novel local search for minimum weighted vertex cover problem. J. Oper. Res. Soc. 71(9), 1498–1509 (2020)
Jain, A.K., Khare, V.K., Mishra, P.M.: Facility planning and associated problems: a survey. Innov. Syst. Des. Eng. 4(6), 1–8 (2013)
Berman, O., Kalcsics, J., Krass, D.: On covering location problems on networks with edge demand. Comput. Oper. Res. 74, 214–227 (2016)
Xiang, X., Qiu, J., Xiao, J., Zhang, X.: Demand coverage diversity based ant colony optimization for dynamic vehicle routing problems. Eng. Appl. Artif. Intell. 91, 103582 (2020)
Klose, A., Drexl, A.: Facility location models for distribution system design. Eur. J. Oper. Res. 162(1), 4–29 (2005)
Lee, S.D., Chang, W.T.: On solving the discrete location problems when the facilities are prone to failure. Appl. Math. Model. 31(5), 817–831 (2007)
Caballero, R., González, M., Guerrero, F.M., Molina, J., Paralera, C.: Solving a multi-objective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia. Eur. J. Oper. Res. 177(3), 1751–1763 (2007)
Alumur, S., Kara, B.Y.: A new model for the hazardous waste location-routing problem. Comput. Oper. Res. 34(5), 1406–1423 (2007)
Berge, C.: Two theorems in graph theory. Proc. Natl. Acad. Sci. USA 43(9), 842–844 (1957)
Gholami, H., Saman, M.Z.M., Sharif, S., Md Khudzari, J., Zakuan, N., Streimikiene, D., Streimikis, J.: A general framework for sustainability assessment of sheet metalworking processes. Sustainability. 12(12), 4957 (2020)
Toregas, C., Swain, R., ReVelle, C., Bergman, L.: The location of emergency service facilities. Oper. Res. 19(6), 1363–1373 (1971)
Crawford, B., Soto, R., Olivares, R., Embry, G., Flores, D., Palma, W., Castro, C., Paredes, F., Rubio, J.M.: A binary monkey search algorithm variation for solving the set covering problem. Nat. Comput. 19(4), 825–841 (2020)
Hashemi, A., Hadavand, S., Esrafilian, R.: An extended mathematical model for multi-floor facility layout problems. Spec. J. Eng. Appl. Sci. 4(1), 69–74 (2019)
Lanza-Gutierrez, J.M., Caballe, N.C., Crawford, B., Soto, R., Gomez-Pulido, J.A., Paredes, F.: Exploring further advantages in an alternative formulation for the set covering problem. Math. Probl. Eng. (2020). https://doi.org/10.1155/2020/5473501
Balas, E., Carrera, M.C.: A dynamic subgradient-based branch-and-bound procedure for set covering. Locat. Sci. 3(5), 203 (1997)
Beasley, J.E.: An algorithm for set covering problem. Eur. J. Oper. Res. 31(1), 85–93 (1987)
Fisher, M.L., Kedia, P.: Optimal solution of set covering/partitioning problems using dual heuristics. Manag. Sci. 36(6), 674–688 (1990)
Jamil, N., Gholami, H., Saman, M.Z.M., Streimikiene, D., Sharif, S., Zakuan, N.: DMAIC-based approach to sustainable value stream mapping: towards a sustainable manufacturing system. Econ. Res.-Ekonomska Istraživanja. 33(1), 331–360 (2020)
Reyes, V., Araya, I.: A GRASP-based scheme for the set covering problem. Oper. Res. (2019). https://doi.org/10.1007/s12351-019-00514-z
Chvatal, V.: A greedy heuristic for the set-covering problem. Math. Oper. Res. 4(3), 233–235 (1979)
Salehipour, A.: A heuristic algorithm for the set k-cover problem. In: International Conference on Optimization and Learning, pp. 98–112. Springer, Cham (2020)
Nogueira, B., Tavares, E., Maciel, P.: Iterated local search with tabu search for the weighted vertex coloring problem. Comput. Oper. Res. 125, 105087 (2021)
Hashemi, A., Esrafilian, R., Hadavand, S., Zeraatkar, M.: Application of fuzzy TOPSIS for evaluation of green supply chain management practices (case study: Zanjan Sepehr Khodro; Iran). Int. J. Eng. Technol. 11(6), 13–24 (2020)
Chiscop, I., Nauta, J., Veerman, B., Phillipson, F.: A hybrid solution method for the multi-service location set covering problem. In: International Conference on Computational Science, pp. 531–545. Springer, Cham (2020)
Wang, Y., Pan, S., Al-Shihabi, S., Zhou, J., Yang, N., Yin, M.: An improved configuration checking-based algorithm for the unicost set covering problem. Eur. J. Oper. Res. 294(2), 476–491 (2021)
Sadeghi, J., Niaki, S.T.A., Malekian, M.R., Wang, Y.: A lagrangian relaxation for a fuzzy random epq problem with shortages and redundancy allocation: two tuned meta-heuristics. Int. J. Fuzzy Syst. 20(2), 515–533 (2018)
Mandal, S., Patra, N., Pal, M.: Covering problem on fuzzy graphs and its application in disaster management system. Soft. Comput. 25(4), 2545–2557 (2021)
Alizadeh, R., Nishi, T.: Hybrid set covering and dynamic modular covering location problem: application to an emergency humanitarian logistics problem. Appl. Sci. 10(20), 7110 (2020)
Lorena, L.A., de Souza Lopes, L.: Genetic algorithms applied to computationally difficult set covering problems. J. Oper. Res. Soc. 48(4), 440–445 (1997)
Aickelin, U.: An indirect genetic algorithm for set covering problems. J. Oper. Res. Soc. 53(10), 1118–1126 (2002)
Idrees, A.K., Al-Yaseen, W.L.: Distributed genetic algorithm for lifetime coverage optimisation in wireless sensor networks. Int. J. Adv. Intell. Paradig. 18(1), 3–24 (2021)
Aourid, M., Kaminska, B.: Neural networks for the set covering problem: an application to the test vector compaction. In: Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), vol. 7, pp. 4645–4649. IEEE (1994)
Yang, Y., Rajgopal, J.: Learning Combined Set Covering and Traveling Salesman Problem. http://arxiv.org/abs/arXiv:2007.03203 (2020).
Vasko, F.J., Wolf, F.E.: A heuristic concentration approach for weighted set covering problems. Locator: ePubl. Locat. Anal. 2(1), 1–14 (2001)
Erkut, E., Alp, O.: Designing a road network for hazardous materials shipments. Comput. Oper. Res. 34(5), 1389–1405 (2007)
Hwang, H.S.: A stochastic set-covering location model for both ameliorating and deteriorating items. Comput. Ind. Eng. 46(2), 313–319 (2004)
Rajagopalan, H.K., Saydam, C., Xiao, J.: A multiperiod set covering location model for dynamic redeployment of ambulances. Comput. Oper. Res. 35(3), 814–826 (2008)
Amoaning-Yankson, S.: A conceptual framework for developing sociotechnical transportation system resilience. PhD diss., Georgia Institute of Technology (2017)
Mandal, S., Patra, N., Pal, M.: Covering problem on fuzzy graphs and its application in disaster management system. Soft Comput. 25(4), 2545–2557 (2020)
Wang, J., Qin, Z.: Chance constrained programming models for uncertain hub covering location problems. Soft. Comput. 24(4), 2781–2791 (2020)
Murray, A.T., Wei, R.: A computational approach for eliminating error in the solution of the location set covering problem. Eur. J. Oper. Res. 224, 52–64 (2013)
Hosseininezhad, S.J., Jabalameli, M.S., Pesaran Haji Abbas, M.: A cross entropy algorithm for continuous covering location problem. J. Ind. Syst. Eng. 11(3), 247–260 (2018)
Bagherinejad, J., Seifbarghy, M., Shoeib, M.: Developing dynamic maximal covering location problem considering capacitated facilities and solving it using hill climbing and genetic algorithm. Eng. Rev.: Međunarodni časopis namijenjen publiciranju originalnih istraživanja s aspekta analize konstrukcija, materijala i novih tehnologija u području strojarstva, brodogradnje, temeljnih tehničkih znanosti, elektrotehnike, računarstva i građevinarstva. 37(2), 178–193 (2017)
Furini, F., Ljubić, I., Sinnl, M.: An effective dynamic programming algorithm for the minimum-cost maximal knapsack packing problem. Eur. J. Oper. Res. 262(2), 438–448 (2017)
Al-Shihabi, S.: A hybrid of max–min ant system and linear programming for the k-covering problem. Comput. Oper. Res. 76, 1–11 (2016)
Dastmardi, M., Mohammadi, M., Naderi, B.: Maximal covering salesman problems with average travelling cost constrains. Int. J. Math. Oper. Res. 17(2), 153–169 (2020)
Bagheri, H., Babaei Morad, S.B.M., Behnamian, J.: Fuzzy multi-period mathematical programming model for maximal covering location problem. J. Ind. Syst. Eng. 11(1), 223–243 (2018)
Shi, H., Yin, B., Zhang, X., Kang, Y., Lei, Y.: A landmark selection method for L-Isomap based on greedy algorithm and its application. In: 2015 54th IEEE Conference on Decision and Control (CDC), pp. 7371–7376. IEEE (2015)
Khorsi, M., Chaharsooghi, S.K., Bozorgi-Amiri, A., Kashan, A.H.: A multi-objective multi-period model for humanitarian relief logistics with split delivery and multiple uses of vehicles. J. Syst. Sci. Syst. Eng. 29, 360–378 (2020)
Mahrach, M., Miranda, G., León, C., Segredo, E.: Comparison between single and multi-objective evolutionary algorithms to solve the knapsack problem and the travelling salesman problem. Mathematics (2018). https://doi.org/10.3390/math8112018
Bogue, E.T., Ferreira, H.S., Noronha, T.F., Prins, C.: A column generation and a post optimization VNS heuristic for the vehicle routing problem with multiple time windows. Optim. Lett. (2020). https://doi.org/10.1007/s11590-019-01530-w
Alamatsaz, K., Jolfaei, A., Iranpoor, M.: Edge covering with continuous location along the network. Int. J. Ind. Eng. Comput. 11(4), 627–642 (2020)
Kaur, C., Misra, N.: On the parameterized complexity of spanning trees with small vertex covers. In: Conference on Algorithms and Discrete Applied Mathematics, pp. 427–438. Springer, Cham (2020)
Klostermeyer, W.F., Messinger, M.E., Yeo, A.: Dominating vertex covers: the vertex-edge domination problem. Discussiones Mathematicae: Graph Theory 41(1), 123–132 (2021)
Fiorini, S., Joret, G., Schaudt, O.: Improved approximation algorithms for hitting 3-vertex paths. Math. Program 182(1), 355–367 (2020)
Redi, A.A.N.P., Maula, F.R., Kumari, F., Syaveyenda, N.U., Ruswandi, N., Khasanah, A.U., Kurniawan, A.C.: Simulated annealing algorithm for solving the capacitated vehicle routing problem: a case study of pharmaceutical distribution. Jurnal Sistem dan Manajemen Industri. 4(1), 41–49 (2020)
Kaur, M., Saini, S.: A review of metaheuristic techniques for solving university course timetabling problem. In: Goar V., Kuri M., Kumar R., Senjyu T. (eds) Advances in Information Communication Technology and Computing. Lecture Notes in Networks and Systems, vol. 135. Springer, Singapore (2021). https://doi.org/10.1007/978-981-15-5421-6_3
Mori, T.: The New Experimental Design: Taguchi’s Approach to Quality Engineering. ASI Press, Dearborn (1990)
Park, S.H.: Robust Design and Analysis for Quality Engineering, 1st edn. Chapman & Hall, London (1996)
Acknowledgements
The authors would like to thank the Research Management Centre at Universiti Teknologi Malaysia and the Ministry of Higher Education (Malaysia) for supporting and funding the Postdoctoral Fellowship scheme (PDRU Grant), Vot No. Q.J130000.21A2.05E33.
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
About this article
Cite this article
Hashemi, A., Gholami, H., Venkatadri, U. et al. A New Direct Coefficient-Based Heuristic Algorithm for Set Covering Problems. Int. J. Fuzzy Syst. 24, 1131–1147 (2022). https://doi.org/10.1007/s40815-021-01208-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40815-021-01208-5