Minimum cost flow problems in generalized fuzzy environments : credibilistic CVaR minimization approach

• Autorzy: Akdemir Hande Günay , Kara Nurdan , Kocken Hale Gonce

Identyfikatory

DOI

10.37190/ord240307

• Języki publikacji: EN

Abstrakty

EN

The paper focuses on the problems of linear programming (LP) with generalized fuzzy numbers (GFNs) as coefficients of the objective function. It is necessary to characterize consistent arithmetic operations to lower the error and information loss compared to the minimum operator usage and normalization in cases where experts are not completely certain of their subjective opinions. The uncertainty is eliminated using the total cost as a loss function and credibilistic conditional value at risk (CVaR) minimization. To crispify and generate a GFN, we utilize a ranking function that allows us to consider risky realizations. By solving many deterministic problems with LP solvers, projections of the error in the objective function can be presented. To describe and implement our methodology, we mainly focus on network optimization problems, especially generalized fuzzy transportation, assignment, and shortest path problems.

Słowa kluczowe

EN

conditional value at risk; credibility distribution function; generalized fuzzy numbers; minimum cost flow problem; ranking function

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2024
• Tom: Vol. 34, No. 3
• Strony: 125--141
• Opis fizyczny: Bibliogr. 33 poz., rys.

Twórcy

autor

Akdemir Hande Günay

• Department of Mathematics, Giresun University, Giresun, Turkey

• https://orcid.org/0000-0003-3241-1560

autor

Kara Nurdan

• Naval Training and Education Command, Turkish Naval Forces, Kocaeli, Turkey

• https://orcid.org/0000-0001-6195-288X

autor

Kocken Hale Gonce

• Department of Mathematical Engineering, Yildiz Technical University, Istanbul, Turkey

• https://orcid.org/0000-0003-1121-7099

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).