dc.creatorDe Franca F.O.
dc.creatorVon Zuben F.J.
dc.creatorDe Castro L.N.
dc.date2004
dc.date2015-06-26T14:25:22Z
dc.date2015-11-26T14:14:59Z
dc.date2015-06-26T14:25:22Z
dc.date2015-11-26T14:14:59Z
dc.date.accessioned2018-03-28T21:15:51Z
dc.date.available2018-03-28T21:15:51Z
dc.identifier780386086
dc.identifierMachine Learning For Signal Processing Xiv - Proceedings Of The 2004 Ieee Signal Processing Society Workshop. , v. , n. , p. 755 - 764, 2004.
dc.identifier
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-17644416124&partnerID=40&md5=1f0813bb2fd3ff14a3512a0cb2c46fc2
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/94734
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/94734
dc.identifier2-s2.0-17644416124
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1242671
dc.descriptionThis work introduces a modified MAX MIN Ant System (MMAS) designed to solve the Capacitated Clustering Problem (CCP). Some improvements on the original MMAS algorithm are proposed, such as the use of a density model on the information heuristic and a local search adapted from the uncapacitated p-medians problem. Also the MMAS ability to deal with large scale instances is improved by means of a new proposal for the pheromone updating rule. Some simulations are performed using instances available from the literature, for benchmarking purposes. As a practical application, given a hypothetical demand proportional to the number of inhabitants of the 186 most populated Brazilian cities, the optimal allocation for a varied number of clustering centers is properly determined by the proposed algorithm, with a superior performance when compared with the original MMAS algorithm. © 2004 IEEE.
dc.description
dc.description
dc.description755
dc.description764
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dc.descriptionBlum, C., Roli, A., Dorigo, M., HC-ACO: The hyper-cube framework for Ant Colony Optimization (2001) Proceedings of MIC'2001 - Meta-heuristics International Conference, 2, pp. 399-403. , Porto, Portugal
dc.descriptionBlum, C., Dorigo, M., The hyper-cube framework for ant colony optimization (2004) IEEE Transactions on Systems, Man and Cybernetics, Part B, 34 (2), pp. 1161-1172
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dc.descriptionAhmadi, S., Osman, I.H., Density based problem space search for the capacitated clustering problem (2004) Annals for Operational Research, , in press
dc.descriptionResende, G.C.M., Werneck, F.R., On the implementation of a swap-based local search procedure for the p-median problem (2003) Proceedings of the Fifth Workshop on Algorithm Engineering and Experiments (ALENEX'03), pp. 119-127. , Richard E. Ladner (Ed.), SIAM, Philadelphia
dc.descriptionTeitz, M.B., Bart, P., Heuristic methods for estimating the generalized vertex median of a weighted graph (1968) Operation Research, 16 (5), pp. 955-961
dc.descriptionLorena, L.A.N., Senne, E.L.F., Local search heuristics for capacitated P-median problems (2003) Networks and Spatial Economics, 3, pp. 407-419
dc.descriptionDe França, F.O., Von Zuben, F.J., De Castro, L.N., A Max Min Ant System Applied to the Capacitated P-Medians Problem, , in preparation
dc.descriptionGomes, L.C.T., Von Zuben, F.J., Multiple criteria optimization based on unsupervised learning and fuzzy inference applied to the vehicle routing problem (2003) Journal of Intelligent & Fuzzy Systems, 13 (2-4), pp. 143-154. , IOS Press
dc.languageen
dc.publisher
dc.relationMachine Learning for Signal Processing XIV - Proceedings of the 2004 IEEE Signal Processing Society Workshop
dc.rightsfechado
dc.sourceScopus
dc.titleA Max Min Ant System Applied To The Capacitated Clustering Problem
dc.typeActas de congresos


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