Estudo Geralhttps://estudogeral.sib.uc.ptThe DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Wed, 13 Nov 2019 16:47:19 GMT2019-11-13T16:47:19Z5041A dynamic location problem with maximum decreasing capacitieshttp://hdl.handle.net/10316/7912Title: A dynamic location problem with maximum decreasing capacities
Authors: Dias, Joana; Captivo, M.; Clímaco, João
Abstract: Abstract In this paper a capacitated dynamic location problem with opening, closure and reopening of facilities is formulated and a primal-dual heuristic that can solve this problem is described. The problem formulated considers the situation where a facility is open (or reopens) with a certain maximum capacity that decreases as clients are assigned to that facility during its operating periods. This problem is NP-hard. Computational results are presented and discussed.
Tue, 01 Jan 2008 00:00:00 GMThttp://hdl.handle.net/10316/79122008-01-01T00:00:00ZA memetic algorithm for multi-objective dynamic location problemshttp://hdl.handle.net/10316/7914Title: A memetic algorithm for multi-objective dynamic location problems
Authors: Dias, Joana; Captivo, M.; Clímaco, João
Abstract: Abstract This paper describes a new multiobjective interactive memetic algorithm applied to dynamic location problems. The memetic algorithm integrates genetic procedures and local search. It is able to solve capacitated and uncapacitated multi-objective single or multi-level dynamic location problems. These problems are characterized by explicitly considering the possibility of a facility being open, closed and reopen more than once during the planning horizon. It is possible to distinguish the opening and reopening periods, assigning them different coefficient values in the objective functions. The algorithm is part of an interactive procedure that asks the decision maker to define interesting search areas by establishing limits to the objective function values or by indicating reference points. The procedure will be applied to some illustrative location problems.
Tue, 01 Jan 2008 00:00:00 GMThttp://hdl.handle.net/10316/79142008-01-01T00:00:00ZA comprehensive survey on the quickest path problemhttp://hdl.handle.net/10316/7731Title: A comprehensive survey on the quickest path problem
Authors: Pascoal, Marta; Captivo, M.; Clímaco, João
Abstract: Abstract This work is a survey on a special minsum-maxmin bicriteria problem, known as the quickest path problem, that can model the transmission of data between two nodes of a network. Moreover, the authors review the problems of ranking the K quickest paths, and the K quickest loopless paths, and compare them in terms of the worst-case complexity order. The classification presented led to the proposal of a new variant of a known K quickest loopless paths algorithm. Finally, applications of quickest path algorithms are mentioned, as well as some comparative empirical results.
Sun, 01 Jan 2006 00:00:00 GMThttp://hdl.handle.net/10316/77312006-01-01T00:00:00ZComputational experiments with a lazy version of a K quickest simple path ranking algorithmhttp://hdl.handle.net/10316/7718Title: Computational experiments with a lazy version of a K quickest simple path ranking algorithm
Authors: Pascoal, M.; Captivo, M.; Clímaco, J.
Abstract: Abstract The quickest path problem is related to the classical shortest path problem, but its objective function concerns the transmission time of a given amount of data throughout a path, which involves both cost and capacity. The K-quickest simple paths problem generalises the latter, by looking for a given number K of simple paths in non-decreasing order of transmission time. Two categories of algorithms are known for ranking simple paths according to the transmission time. One is the adaptation of deviation algorithms for ranking shortest simple paths (Pascoal et al. in Comput. Oper. Res. 32(3):509–520, 2005; Rosen et al. in Comput. Oper. Res. 18(6):571–584, 1991), and another is based on ranking shortest simple paths in a sequence of networks with fixed capacity lower bounds (Chen in Inf. Process. Lett. 50:89–92, 1994), and afterwards selecting the K quickest ones. After reviewing the quickest path and the K-quickest simple paths problems we describe a recent algorithm for ranking quickest simple paths (Pascoal et al. in Ann. Oper. Res. 147(1):5–21, 2006). This is a lazy version of Chen’s algorithm, able to interchange the calculation of new simple paths and the output of each k-quickest simple path. Finally, the described algorithm is computationally compared to its former version, as well as to deviation algorithms.
Mon, 01 Jan 2007 00:00:00 GMThttp://hdl.handle.net/10316/77182007-01-01T00:00:00Z