Abstract
The generalized vertex cover problem (GVC) is a new variant of classic vertex cover problem which considers both vertex and weight of the edge into the objective function. The GVC is a renowned NP-hard optimization problem that finds the vertex subset where the sum of vertices and edge weight are minimized. In the mathematical field of electrical, networking and telecommunication GVC is used to solve the vertex cover problem. Finding the minimum vertex cover using GVC has a great impact on graph theory. Some exact algorithms were proposed to solve this problem, but they failed to solve it for real-world instances. Some approximation and metaheuristic algorithms also were proposed to solve this problem. Chemical Reaction Optimization (CRO) is an established population-based metaheuristic for optimization and comparing with other existing optimization algorithms it gives better results in most of the cases. The CRO algorithm helps to explore the search space locally and globally over the large population area. In this paper, we are proposing an algorithm by redesigning the basic four operators of CRO to solve GVC problem and an additional operator named repair function is used to generate optimal or near-optimal solutions. We named the proposed algorithm as GVC_CRO. Our proposed GVC_CRO algorithm is compared with the hybrid metaheuristic algorithm (MAGVCP), the local search with tabu strategy and perturbation mechanism (LSTP) and Genetic Algorithm (GA), which are state of the arts. The experimental results show that our proposed method gives better results than other existing algorithms to solve the GVC problem with less execution time in maximum cases. Statistical test has been performed to demonstrate the superiority of the proposed algorithm over the compared algorithm.












Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Cai S, Su K, Chen Q (2010) Ewls: A new local search for minimum vertex cover. In: AAAI
Guo J, Niedermeier R, Wernicke S (2007) Parameterized complexity of vertex cover variants. Theory Comput Syst 41(3):501–520
Hassin R, Levin A (2003) The minimum generalized vertex cover problem. In: European symposium on algorithms, pp 289-300. Springer
Hu S, Li R, Zhao P, Yin M (2018) A hybrid metaheuristic algorithm for generalized vertex cover problem. Memetic Computing 10(2):165–176
Islam MR, Saifullah CMK, Asha ZT, Ahmet R (2018) Chemical reaction optimization for solving longest common subsequence problem for multiple string. Soft Comput 1–25. https://doi.org/10.1007/s00500-018-3200-3 https://doi.org/10.1007/s00500-018-3200-3
James JQ, Lam AYS (2011) Victor OK Li. Evolutionary artificial neural network based on chemical reaction optimization. In: IEEE congress on evolutionary computation (CEC), pp 2083-2090, IEEE, pp 2011
Kabir R, Islam R (2018) Chemical reaction optimization for rna structure prediction. Appl Intell 1–24. https://doi.org/10.1007/s10489-018-1281-4 https://doi.org/10.1007/s10489-018-1281-4
Karakostas G (2009) A better approximation ratio for the vertex cover problem. ACM Trans Algorithms (TALG) 5(4):41
Karp RM (1972) Reducibility among combinatorial problems, pp 85-103. In: Miller RE, Thatcher JW (eds) Complexity of computer computations
Kochenberger G, Lewis M, Glover F, Wang H (2015) Exact solutions to generalized vertex covering problems: a comparison of two models. Optim Lett 9(7):1331–1339
Lam AYS, Li VOK (2012) Chemical reaction optimization: a tutorial. Memetic Computing 4(1):3–17
Li R, Hu S, Wang Y, Yin M (2017) A local search algorithm with tabu strategy and perturbation mechanism for generalized vertex cover problem. Neural Comput & Applic 28(7):1775– 1785
Milanovi M (2012) Solving the generalized vertex cover problem by genetic algorithm. Commun Inf 29 (6+):1251–1265
Saifullah KCM, Islam MR (2016) Chemical reaction optimization for solving shortest common supersequence problem. Comput Biol Chem 64:82–93
Truong TK, Li K, Xu Y (2013) Chemical reaction optimization with greedy strategy for the 0-1 knapsack problem. Appl Soft Comput 13(4):1774–1780
Xu J, Lam AYS, Li VOK (2010) Parallel chemical reaction optimization for the quadratic assignment problem. In: World Congress in Computer Science, Computer engineering, and applied computing, Worldcomp 2010
Xu J, Lam AYS, Li VOK (2011) Chemical reaction optimization for task scheduling in grid computing. IEEE Trans Parallel Distrib Syst 22(10):1624–1631
Pooja P, Punnen AP (2018) The generalized vertex cover problem and some variations. Discrete Optimization
Bugra C et al (2014) On partial vertex cover and budgeted maximum coverage problems in bipartite graphs. In: IFIP international conference on theoretical computer science. Springer, Berlin
Reuven B-Y, Hermelin D, Rawitz D (2010) An extension of the Nemhauser-Trotter theorem to generalized vertex cover with applications. SIAM J Discret Math 24.1:287–300
Oliveto PS, He J, Yao X (2007) Evolutionary algorithms and the vertex cover problem. In: IEEE congress on evolutionary computation, 2007. CEC 2007. IEEE
Jochen K, Parekh O, Segev D (2006) A unified approach to approximating partial covering problems.European symposium on algorithms. Springer, Berlin
Mitchell M (2003) Genetic algorithms. pp 747-748
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interests
The authors have no conflict of interest.
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
Islam, M.R., Arif, I.H. & Shuvo, R.H. Generalized vertex cover using chemical reaction optimization. Appl Intell 49, 2546–2566 (2019). https://doi.org/10.1007/s10489-018-1391-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10489-018-1391-z