Theory and methodologyA review of extensive facility location in networks
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Cited by (61)
A linear time algorithm for connected p-centdian problem on block graphs
2022, Theoretical Computer ScienceEfficient algorithms for the minmax regret path center problem with length constraint on trees
2022, Theoretical Computer ScienceCitation Excerpt :The problems of locating extensive facilities have been comprehensively studied in the literature [3,13,26,28,31,35–39]. For excellent surveys of extensive facility location problems, we refer to [25,30]. A network usually involves two types of parameters: weights of nodes and lengths of edges.
Locating a discrete subtree of minimum variance on trees: New strategies to tackle a very hard problem
2021, Discrete Applied MathematicsAn improved algorithm for the minmax regret path center problem on trees
2020, Journal of Computer and System SciencesCitation Excerpt :The problems of locating points and extensive facilities on the center and median models have been comprehensively studied in the literature [3,12,20,21,25,27,30,34–36]. For excellent surveys of extensive facility location problems on networks, we refer to [24,29]. A network usually involves two types of parameters: weights of nodes and lengths of edges.
The bi-objective insular traveling salesman problem with maritime and ground transportation costs
2018, European Journal of Operational ResearchCitation Excerpt :Whereas, in this study, the demands associated to unselected nodes must be served using other selected nodes. Other related works that model the assignment of non-visited nodes to the visited nodes can be named Extended Network Design Problems or known as Extensive Facility Location Problems (Labbé et al., 1998; Mesa and Boffey, 1996; Pop, 2012). The aim of these problems is to search for a main or principal transportation structure such as paths, tours, or trees, by selecting and connecting a subset of nodes, and a secondary transportation component for serving the non-selected nodes to the main structure of the selected nodes.
Hybrid evolutionary algorithm with extreme machine learning fitness function evaluation for two-stage capacitated facility location problems
2017, Expert Systems with Applications