A New Neurodynamics-Based Model for Fuzzy Convex Optimization Problems with Fuzzy Coefficients and General Constraints

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dc.authorscopusidWitold Pedrycz / 58861905800
dc.authorwosidWitold Pedrycz / HJZ-2779-2023
dc.contributor.authorChen, Jiqiang
dc.contributor.authorMa, Litao
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2025-04-16T20:23:18Z
dc.date.available2025-04-16T20:23:18Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractFuzzy convex optimization problems with fuzzy coefficients (FCOPFCs) arise in many applications. Although many neurodynamics-based models have been proposed for solving FCOPFCs, most of them are designed for FCOPFCs with equality or inequality constraints only. However, in many applications, the FCOPFCs often come with both equality and inequality constraints (general constraints, for short), so most of the neurodynamics-based models no longer work in these situations. Therefore, this article aims to construct a new model for FCOPFCs with general constraints to extend the applications of neurodynamics-based models. First of all, based on fuzzy set theory, the original FCOPFCs with general constraints is transformed into a series of interval programming tasks and further transformed into crisp optimization problems with weights. Then, a novel continuous-time neurodynamics-based model with a single-layer structure is established to solve the crisp optimization problem with weights. Further, we discuss the global existence and prove the stability of state solutions. The theoretical results show that the state solutions reach the feasible region within finite time and converge to the optimal solution with the smallest 2-norm. Simulation results completed for three kinds of FCOPFCs show the validity of the approach, and the results in real-world applications demonstrate the excellent performance of the proposed model. © 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation of China under Grant 62006068, in part by the Natural Science Foundation of Hebei Province under Grant A2021402008, in part by the Natural Science Foundation of Scientific Research Project of Higher Education in Hebei Province under Grant ZD2020185 and Grant QN2020188. Recommended byAssociate Editor P.Gupta.
dc.identifier.citationChen, J., Ma, L., Pedrycz, W., & Wang, X. (2024). A New Neurodynamics-Based Model for Fuzzy Convex Optimization Problems With Fuzzy Coefficients and General Constraints. IEEE Transactions on Fuzzy Systems.
dc.identifier.doi10.1109/TFUZZ.2024.3411049
dc.identifier.endpage5085
dc.identifier.issn10636706
dc.identifier.issue9
dc.identifier.scopusqualityQ1
dc.identifier.startpage5073
dc.identifier.urihttp://dx.doi.org/10.1109/TFUZZ.2024.3411049
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6076
dc.identifier.volume32
dc.identifier.wosWOS:001307418200012
dc.identifier.wosqualityQ1
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorPedrycz, Witold
dc.institutionauthoridWitold Pedrycz / 0000-0002-9335-9930
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIEEE Transactions on Fuzzy Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectConvex Programming
dc.subjectFuzzy Optimization
dc.subjectGeneral Constraints
dc.subjectNeurodynamic Model
dc.titleA New Neurodynamics-Based Model for Fuzzy Convex Optimization Problems with Fuzzy Coefficients and General Constraints
dc.typeArticle

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