Caprara, A., Toth, P. & Fischetti, M. (2000), Algorithms for the Set Covering Problem, Annals of Operations Research 98, 353--371. Home/Search Document Details and Download
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A Hybrid Algorithm for Set Covering Problem - Eremeev, Kolokolov, Zaozerskaya (Correct)
....and only if i 2 M j . Using this formulation one can view SCP as a problem of optimal covering of rows by the columns in matrix A . In this paper we assume that the columns are ordered according to nonincreasing values of c j s. Amoung the numerous applications of the SCP are the crew scheduling [2, 7], emergency facilities allocation, production flow lines optimization [6] etc. Different algorithms have been proposed for exact The research was supported in part by RFBR Grant 9701 00771, and INTAS Grant 96 0820. solving of SCP using branch and bound approach [2, 5, 17] cutting planes, ....
....application of exact algorithms to the large scale instances is very timeconsuming. A number of heuristic algorithms are developed for approximate solving the large scale problems within relatively short running time. The solutions of good quality may be obtained using Lagrangean heuristics [7], neural networks [14] or metaheuristics such as GA [4, 11] or ant colony algorithms [1] Most of the successful versions of exact algorithms combine the exact techniques with heuristic methods (see e.g. 2, 5] 2. L CLASS ENUMERATION FOR The papers [15, 18] and some other works are devoted to ....
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Caprara A., Fischetti M., Toth P. Algorithms for the Set Covering Problem, Technical Report OR98 -3, DEIS-Operations Research Group, 1998.
A Genetic Algorithm with a Non-Binary Representation for the Set.. - Eremeev (1999) (2 citations) (Correct)
....usually application of exact algorithms to the large scale instances is very time consuming. A number of heuristic algorithms are developed for approximate solving the problem within relatively short running time. The solutions of good quality may be obtained using Lagrangian relaxation heuristics [4], neural networks [10] or metaheuristics such as GA [3] 2. Genetic Algorithm GA is a probabilistic search method based on biological analogy of selective breeding in nature, used for the search of near optimal solutions. The basic components of GA are a population of individuals and random ....
....720 737 328 341 171 180 91 96 808 817 353 370 Density ( 2 2 5 2 5 2 5 10 20 2 5 Num. of probl. 10 10 5 5 5 5 5 5 5 5 5 Table 1. Tables 2 and 3 compare the performance of the NBGA to the performance of GA by Beasley and Chu [3] BC) and the Lagrangian heuristic by Caprara, Fischetti and Toth [4] (CFT) In our experiments 10 trials of GA were made for each problem with the settings s = 100, pm = 0:1, t max = 10000. The column oe represents the average percentage deviation P 10 k=1 z k Gammaz 10z Delta 100 , where z k is the solution found in k th trial and z is the optimal or ....
[Article contains additional citation context not shown here]
A. Caprara, M. Fischetti, P. Toth. Algorithms for the Set Covering Problem. Technical Report No. OR-98-3. DEIS-Operations Research Group, 1998.
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Caprara, A., Toth, P. & Fischetti, M. (2000), Algorithms for the Set Covering Problem, Annals of Operations Research 98, 353--371.
Minimizing Operations Costs for a Container Road Carrier - Luca Coslovich Raaele (2003) (Correct)
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A. Caprara, P. Toth, M. Fischetti, Algorithms for the Set Covering Problem, Annals of Operations Research, 98 (2000) 353--371.
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A. Caprara, M. Fischetti, and P. Toth, "Algorithms for the Set Covering Problem," Tech. Rep. No. OR-98-3, DEIS-Operations Research Group, 1998.
An Indirect Genetic Algorithm for Set Covering Problems - Aickelin (2002) (2 citations) (Correct)
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Caprara A, Fischetti M and Toth P (1999), Algorithms for the Set Covering Problem, working paper, DEIS, University of Bologna, Italy.
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