109590 20241125101123.0 doi 10.1111/itor.12943 sideral 123289 ART-2023-123289 eng Calvete, Herminia I. Universidad de Zaragoza (orcid)0000-0001-7603-9380 A decision tool based on bilevel optimization for the allocation of water resources in a hierarchical system 2023 Access copy available to the general public Unrestricted This paper addresses the optimal allocation of water among competing stakeholders during a finite planning horizon. We focus on those water systems where there are two levels of decision making organized according to a hierarchical framework. At the upper level, a central authority allocates water to demand points having regard to environmental and sustainability issues as well as balancing water users' supply/demand. At the lower level of the hierarchy, demand point managers allocate water to users prioritizing economic strategies. On the other hand, when it comes to allocating limited resources that affect public welfare, the authority in charge can also use different political instruments such as fees to influence the decisions made at those levels of decision making that are not directly within its competence. We propose a multiobjective multifollower bilevel optimization problem that aims to fulfill the central authority goals while including the reaction of the demand point managers in terms of optimization problems as constraints. Using the well-known Karush–Kuhn–Tucker approach, we transform the bilevel model into an equivalent multiobjective mixed-integer single-level model for which we provide tight big-M values. For the purpose of showing the versatility of the model, extensive computational experiments on a set of instances have been carried out. The results show that the optimization problem can be solved to optimality in small computing times using off-the-shelf mixed-integer solvers even for complex water systems and long planning periods. In addition, they illustrate the effect of imposing fees on the achievement of the central authority's objectives. info:eu-repo/grantAgreement/ES/DGA/E41-20R info:eu-repo/grantAgreement/ES/DGA-FEDER/Construyendo Europa desde Aragón info:eu-repo/grantAgreement/ES/DGA-FEDER/E41-17R info:eu-repo/grantAgreement/ES/MICINN/PID2019-104263RB-C43 info:eu-repo/grantAgreement/ES/MINECO/ECO2016-76567-C4-3-R info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 3.1 2023 MANAGEMENT 171 / 407 = 0.42 2023 Q2 T2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE 34 / 106 = 0.321 2023 Q2 T1 1.027 2023 Business and International Management 2023 Q1 Computer Science Applications 2023 Q1 Strategy and Management 2023 Q1 Management Science and Operations Research 2023 Q1 Management of Technology and Innovation 2023 Q2 7.8 2023 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Galé, Carmen Universidad de Zaragoza (orcid)0000-0002-5630-3719 Iranzo, José A. Universidad de Zaragoza (orcid)0000-0001-9993-9816 Mateo, Pedro M. Universidad de Zaragoza (orcid)0000-0003-2988-7728 2007 265 Universidad de Zaragoza Dpto. Métodos Estadísticos Área Estadís. Investig. Opera. 30, 4 (2023), 1673-1702 Int. trans. oper. res. INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 0969-6016 640577 http://zaguan.unizar.es/record/109590/files/texto_completo.pdf Postprint 1722217 http://zaguan.unizar.es/record/109590/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:109590 articulos driver 2024-11-22-11:57:00 ARTICLE