Yazar "Lotfi, Farhad Hosseinzadeh" seçeneğine göre listele

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    Fully interval-valued fuzzy transportation problems: development and prospects
    (Springer Heidelberg, 2024) Peng, Zhihao; Nikbakht, Maryam; Ebrahimnejad, Ali; Lotfi, Farhad Hosseinzadeh; Allahviranloo, Tofigh
    The transportation problem (TP) is one of the most used and tangible applications of linear programming problems that apply to a variety of practical settings. The main objective of this problem is to find an optimal transfer plan with the minimum cost of shipping the goods so that the demands of the destinations are satisfied using the supplies available at the sources. Conventional TPs generally assume that the values of transportation costs and the values of demand and supply are defined by real variables, though these values are unpredictable in TPs due to some uncontrollable factors. The present study formulates a TP when all parameters are interval-valued trapezoidal fuzzy numbers and uses a novel optimization structure to obtain the efficient solution of the resulting problem. The novelty of such optimization process resides in that it requires less computations effort as opposed to the existing methods. The applicability of the proposed approach is illustrated through a numerical example.
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    Interval model for calculating prospect cross efficiency of data envelopment analysis and providing a solution for its expansion in fuzzy model
    (SEMNAN UNIV, 2021) Rahmani, Amir; Rostamy-Malkhalifeh, Mohsen; Lotfi, Farhad Hosseinzadeh; Allahviranloo, Tofigh
    Cross efficiency evaluation of data envelopment analysis (DEA) is an effective tool in measuring the performance of decision-making units. In general, in cross efficiency evaluation models, it is assumed that decision makers are completely rational, in which case they refrain from considering the risk attitude that plays an important role in the evaluation process. In order to fill this gap, cross efficiency evaluation in DEA was performed based on prospect theory. In the real world, many inputs and outputs are not known, which are called inaccurate data; what is expected is that even if one of the data is not accurate, the answer will probably not be accurate. To solve this problem, the present study presents models that are able to evaluate the prospect cross efficiency with interval data and proves the feasibility of the models by proving the theorems.