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Fuzzy type-II De-Novo programming for resource allocation and target setting in network data envelopment analysis: A natural gas supply chain.

Authors :
J.-Sharahi, Sarah
Khalili-Damghani, Kaveh
Source :
Expert Systems with Applications. Mar2019, Vol. 117, p312-329. 18p.
Publication Year :
2019

Abstract

Highlights • An uncertain resource allocation-targets setting approach is proposed. • Uncertainties of resources and targets are modeled using type-II & type I fuzzy sets. • Fuzzy De-Novo programming for resource allocation and target setting is developed. • A real case of the natural gas supply chain is analyzed. Abstract Developing effective approaches to design optimal resources of system based on the concepts of benchmark in DEA and optimal design in De-Novo programming is one of the important managerial decision making problems. In this paper, a decision support system is developed for allocation of resources and setting the targets across a set of entities in an equitable manner in presence of uncertainty. The proposed approach has two main modules. First, the most suitable system is designed using De-Novo programming. De-Novo programming. De-Novo programming is used to optimally determine the inputs (i.e., resources) and outputs (i.e., targets) of DMUs in network DEA rather than optimizing existing DMUs. Then, the optimal values of resources are allocated and optimal values of the targets are set in a complex network structure. Furthermore, in real-world problems budget of resources and targets are usually mixed with uncertainties, so in this paper, two concept of fuzzy and interval type-II fuzzy resources and target are developed for resource allocation and target setting. Finally numerical example based on real case of natural gas supply chain is also used to evaluate the applicability and efficacy of the proposed models. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09574174
Volume :
117
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
132606491
Full Text :
https://doi.org/10.1016/j.eswa.2018.09.046