Identifying the Influential Factors in Increasing the Efficiency of Network Systems: A Mixed Binary Linear Programming

Old models in data envelopment analysis (DEA) consider decision-making units (DMUs) as black boxes. Therefore, they do not have a proper efficiency to evaluate network systems. This shortcoming has led to the emergence of network models that take the performance of a system’s processes into account...

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Vydáno v:Operations Research Forum Ročník 4; číslo 4; s. 68
Hlavní autoři: Feizabadi, Reza, Bagherian, Mehri
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 01.12.2023
Springer Nature B.V
Témata:
Airlines
Applications of Mathematics
Business and Management
Data envelopment analysis
Decision analysis
Efficiency
Linear programming
Math Applications in Computer Science
Mathematical and Computational Engineering
Operations Research/Decision Theory
Optimization
Performance evaluation
Taiwan
Data envelopment analysis (DEA)
Intermediate factors
Mixed binary linear programming
Network systems
ISSN:2662-2556, 2662-2556
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Shrnutí:Old models in data envelopment analysis (DEA) consider decision-making units (DMUs) as black boxes. Therefore, they do not have a proper efficiency to evaluate network systems. This shortcoming has led to the emergence of network models that take the performance of a system’s processes into account in calculating the performance, and some of which also assign a certain value of performance to the processes. However, no model has examined the effect of intermediate factors in a network system, while the study of these intermediate factors can greatly help to increase the efficiency of a system. In this paper, our aim is to present a mixed binary linear programming that identifies the intermediate factors that are relatively more effective in increasing the performance of a network system. At the end, the new model is implemented on a small network system in order to better describe the performance, as well as on a real-world network system.
Bibliografie:ObjectType-Article-1
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ISSN:2662-2556
2662-2556
DOI:10.1007/s43069-023-00259-8