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Soft Computing
Erschienen in: Soft Computing 13/2020

12.11.2019 | Methodologies and Application

Fuzzy linear programming problems: models and solutions

verfasst von: Reza Ghanbari, Khatere Ghorbani-Moghadam, Nezam Mahdavi-Amiri, Bernard De Baets

Erschienen in: Soft Computing | Ausgabe 13/2020

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Abstract

We investigate various types of fuzzy linear programming problems based on models and solution methods. First, we review fuzzy linear programming problems with fuzzy decision variables and fuzzy linear programming problems with fuzzy parameters (fuzzy numbers in the definition of the objective function or constraints) along with the associated duality results. Then, we review the fully fuzzy linear programming problems with all variables and parameters being allowed to be fuzzy. Most methods used for solving such problems are based on ranking functions, \(\alpha \)-cuts, using duality results or penalty functions. In these methods, authors deal with crisp formulations of the fuzzy problems. Recently, some heuristic algorithms have also been proposed. In these methods, some authors solve the fuzzy problem directly, while others solve the crisp problems approximately.
Vorheriger Artikel Adaptive population structure learning in evolutionary multi-objective optimization
Nächster Artikel An enhanced cuckoo optimization algorithm for task graph scheduling in cluster-computing systems

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Metadaten
Titel
Fuzzy linear programming problems: models and solutions
verfasst von
Reza Ghanbari
Khatere Ghorbani-Moghadam
Nezam Mahdavi-Amiri
Bernard De Baets
Publikationsdatum
12.11.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 13/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04519-w

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