A new maximal flow algorithm for solving optimization problems with linguistic capacities and flows

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dc.authoridTofigh Allahviranloo / 0000-0002-3929-9762en_US
dc.authorscopusidTofigh Allahviranloo / 8834494700en_US
dc.authorwosidTofigh Allahviranloo / V-4843-2019en_US
dc.contributor.authorAkram, Muhammad
dc.contributor.authorHabib, Amna
dc.contributor.authorAllahviranloo, Tofigh
dc.date.accessioned2022-11-11T08:11:35Z
dc.date.available2022-11-11T08:11:35Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümüen_US
dc.description.abstractThe maximal flow problems (MFPs) are among the most significant optimization problems in network flow theory with widespread and diverse applications. To represent qualitative aspects of uncertainty in the maximal flow model, which asks for the largest amount of flow transported from one vertex to another, the use of linguistic variables has effective means for experts in expressing their views. In this paper, we first define trapezoidal Pythagorean fuzzy numbers (TrPFNs) along with some new arithmetic operations which cover the gaps in previously defined operations. For defuzzification of TrPFNs, we introduce a ranking procedure based on value and ambiguity indices. This work puts forward a the-oretical framework for a new Pythagorean fuzzy maximal flow algorithm (PFMFA), which helps to solve different optimization problems with PF information by considering linguis-tic capacities and flows. The implementation of the algorithm is elaborated by considering two case studies. Firstly, we examine the maximum flow of a water distribution pipeline network in Pyigyitagon Township, Mandalay, Myanmar. Secondly, we compute maximum PF power flow in a 14-bus electricity network provided by the IEEE working group, con-cerning the example data from the University of Washington. The results illustrate the superiority of the proposed method and give a detailed analysis of flow connected with several practical performances. In addition, the Pythagorean fuzzy optimal flows corre-sponding to each network arc are compared and performance comparison of our method is investigated which shows the increasing and decreasing trends of backward and forward arcs of the network, respectively. Moreover, the runtime analysis of existing well-known maximal flow algorithms is provided. Finally, we present the advantages of our technique to promote its cogency. (c) 2022 Elsevier Inc. All rights reserved.en_US
dc.identifier.citationAkram, M., Habib, A., & Allahviranloo, T. (2022). A new maximal flow algorithm for solving optimization problems with linguistic capacities and flows. Information Sciences, 612, 201-230.en_US
dc.identifier.doi10.1016/j.ins.2022.08.068en_US
dc.identifier.endpage230en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage201en_US
dc.identifier.urihttps://doi.org/10.1016/j.ins.2022.08.068
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3324
dc.identifier.volume612en_US
dc.identifier.wosWOS:000863321400005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAllahviranloo, Tofigh
dc.language.isoenen_US
dc.publisherELSEVIER SCIENCE INCen_US
dc.relation.ispartofINFORMATION SCIENCESen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMaximal Flow Algorithmen_US
dc.subjectWater Pipeline Networken_US
dc.subjectElectricity Networken_US
dc.subjectTrapezoidal Pythagorean Fuzzy Numberen_US
dc.subjectValue and Ambiguity Indicesen_US
dc.subjectLinguistic Variableen_US
dc.titleA new maximal flow algorithm for solving optimization problems with linguistic capacities and flowsen_US
dc.typeArticleen_US

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