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Beni-Suef University Journal of Basic and Applied Sciences
Article . 2018 . Peer-reviewed
License: CC BY NC ND
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Interactive Approach for Multi-Level Multi-Objective Fractional Programming Problems with Fuzzy Parameters

Authors: Mohamed Elsayed; O. E. Emam; Mohamed S. Osman;

Interactive Approach for Multi-Level Multi-Objective Fractional Programming Problems with Fuzzy Parameters

Abstract

In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP) problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997). In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.

Keywords

Fuzzy parameters, Medicine (General), R5-920, Multi-objective programming, Science, Q, Fractional programming, Multi-level programming

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
gold