2026-05-30T05:15:46Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/154792026-02-03T11:54:06Zcom_10630_2254col_10630_37959

Domínguez, Miguel A. Chicano-García, José-Francisco Ruiz-Mora, Ana Belén Domínguez-Merino, Enrique 2018-03-22T12:01:04Z 2018-03-22T12:01:04Z 2018-03-22 https://hdl.handle.net/10630/15479 In many logistic, telecommunications and computer networks, direct routing of commodities between any origin and destination is not viable due to economic and technolog- ical constraints. In that cases, a network with centralized units, known as hub facilities, and a small number of links is commonly used to connect any origin-destination pair. The purpose of these hub facilities is to consolidate, sort and transship e ciently any commodity in the network. Hub location problems (HLPs) consider the design of these networks by locating a set of hub facilities, establishing an interhub subnet, and routing the commodities through the network while optimizing some objective(s) based on the cost or service. Hub location has evolved into a rich research area, where a huge number of papers have been published since the seminal work of O'Kelly [1]. Early works were focused on analogue facility location problems, considering some assumptions to simplify network design. Recent works [2] have studied more complex models that relax some of these assumptions and in- corporate additional real-life features. In most HLPs considered in the literature, the input parameters are assumed to be known and deterministic. However, in practice, this assumption is unrealistic since there is a high uncertainty on relevant parameters, such as costs, demands or even distances. In this work, we will study the multi-objective hub location problems with uncertainty. eng open access Algoritmos computacionales - Congresos Solving multi-objective hub location problems by hybrid algorithms conference output