79083 20220208112845.0 doi 10.1016/j.ejor.2018.02.041 sideral 106378 ART-2018-106378 eng Calvete, H.I. Universidad de Zaragoza (orcid)0000-0001-7603-9380 Dealing with residual energy when transmitting data in energy-constrained capacitated networks 2018 Access copy available to the general public Unrestricted This paper addresses several problems relating to the energy available after the transmission of a given amount of data in a capacitated network. The arcs have an associated parameter representing the energy consumed during the transmission along the arc and the nodes have limited power to transmit data. In the first part of the paper, we consider the problem of designing a path which maximizes the minimum of the residual energy remaining at the nodes. After formulating the problem and proving the main theoretical results, a polynomial time algorithm is proposed based on computing maxmin paths in a sequence of non-capacitated networks. In the second part of the paper, the problem of obtaining a quickest path in this context is analyzed. First, the bi-objective variant of this problem is considered in which we aim to minimize the transmission time and to maximize the minimum residual energy. An exact polynomial time algorithm is proposed to find a minimal complete set of efficient solutions which amounts to solving shortest path problems. Second, the problem of computing an energy-constrained quickest path which guarantees at least a given residual energy at the nodes is reformulated as a variant of the energy-constrained quickest path problem. The algorithms are tested on a set of benchmark problems providing the optimal solution or the Pareto front within reasonable computing times. info:eu-repo/grantAgreement/ES/DGA-FSE/E58 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 3.806 2018 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 13 / 84 = 0.155 2018 Q1 T1 2.205 2018 Computer Science (miscellaneous) 2018 Q1 Modeling and Simulation 2018 Q1 Management Science and Operations Research 2018 Q1 Information Systems and Management 2018 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion del-Pozo, L. Universidad de Zaragoza (orcid)0000-0001-8686-3963 Iranzo, J.A. (orcid)0000-0001-9993-9816 2007 265 Universidad de Zaragoza Dpto. Métodos Estadísticos Área Estadís. Investig. Opera. 269, 2 (2018), 602-620 Eur. J. oper. res. European Journal of Operational Research 0377-2217 968912 http://zaguan.unizar.es/record/79083/files/texto_completo.pdf Postprint 46775 http://zaguan.unizar.es/record/79083/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:79083 articulos driver 2022-02-08-11:23:45 ARTICLE