Abstract
The Minimum Latency Problem (MLP) is a combinatorial optimization problem which has many practical applications. Recently, several approximation algorithms with guaranteed approximation ratio have been proposed to solve the MLP problem. These algorithms start with a set of solutions of the k −MST or k −troll problem, then convert the solutions into Eulerian tours, and finally, concatenate these Eulerian tours to obtain a MLP tour. In this paper, we propose an algorithm based on the principles of the subgradient method. It still uses the set of solutions of the k −MST or k −troll problem as an input, then modifies each solution into a tour with cost smaller than that of Eulerian tour and finally, uses obtained tours to construct a MLP tour. Since the low cost tours are used to build a MLP tour, we can expect the approximation ratio of obtained algorithm will be improved. In order to illustrate this intuition, we have evaluated the algorithm on five benchmark datasets. The experimental results show that approximation ratio of our algorithm is improved compared to the best well-known approximation algorithms.
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References
Archer, A., Levin, A., Williamson, D.: A Faster, Better Approximation Algorithm for the Minimum Latency Problem. J. SIAM 37(1), 1472–1498 (2007)
Arora, S., Karakostas, G.: Approximation schemes for minimum latency problems. In: Proc. ACM STOC, pp. 688–693 (1999)
Ban, H.B., Nguyen, K., Ngo, M.C., Nguyen, D.N.: An efficient exact algorithm for Minimum Latency Problem. J. Progress of Informatics (10), 1–8 (2013)
Blum, A., Chalasani, P., Coppersmith, D., Pulleyblank, W., Raghavan, P., Sudan, M.: The minimum latency problem. In: Proc. ACM STOC, pp. 163–171 (1994)
Chaudhuri, K., Goldfrey, B., Rao, S., Talwar, K.: Path, Tree and minimum latency tour. In: Proc. IEEE FOCS, pp. 36–45 (2003)
Garg, N.: Saving an Epsilon: A 2-approximation for the k −MST Problem in Graphs. In: Proc. STOC, pp. 396–402 (2005)
Goemans, M., Kleinberg, J.: An improved approximation ratio for the minimum latency problem. In: Proc. ACM-SIAM SODA, pp. 152–158 (1996)
Held, M., Karp, R.M.: The travelling salesman problem and minimum spanning tree: part II. J. Mathematical Programming 1, 5–25 (1971)
Motzkin, T., Schoenberg, I.J.: The relaxation method for linear inequalities. J. Mathematics, 393–404 (1954)
Sahni, S., Gonzalez, T.: P-complete approximation problem. J. ACM 23(3), 555–565 (1976)
Salehipour, A., Sorensen, K., Goos, P., Braysy, O.: Efficient GRASP+VND and GRASP+VNS metaheuristics for the traveling repairman problem. J. Operations Research 9(2), 189–209 (2011)
Silva, M., Subramanian, A., Vidal, T., Ochi, L.: A simple and effective metaheuristic for the Minimum Latency Problem. J. Operations Research 221(3), 513–520 (2012)
Rosenkrantz, D.J., Stearns, R.E., Lewis, P.M.: An analysis of several heuristics for the traveling salesman problem. SIAM J. Comput. (6), 563–581 (1977)
Polyak, B.T.: Minimization of unsmooth functionals. U.S.S.R. Computational Mathematics and Mathematical Physis 9(3), 14–29 (1969)
Wu, B.Y., Huang, Z.-N., Zhan, F.-J.: Exact algorithms for the minimum latency problem. Inform. Proc. Letters 92(6), 303–309 (2004)
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Ha, B.B., Duc, N.N. (2014). A Subgradient Method to Improve Approximation Ratio in the Minimum Latency Problem. In: Huynh, V., Denoeux, T., Tran, D., Le, A., Pham, S. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 244. Springer, Cham. https://doi.org/10.1007/978-3-319-02741-8_29
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DOI: https://doi.org/10.1007/978-3-319-02741-8_29
Publisher Name: Springer, Cham
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