Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/267627 
Year of Publication: 
2019
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 15 [Issue:] 2 [Publisher:] Springer [Place:] Heidelberg [Year:] 2019 [Pages:] 315-331
Publisher: 
Springer, Heidelberg
Abstract: 
This paper proposes an innovative procedure of finding efficient facility location-allocation (FLA) schemes, integrating data envelopment analysis (DEA) and a multi-objective programming (MOP) model methodology. FLA decisions provide a basic foundation for designing efficient supply chain network in many practical applications. The procedure proposed in this paper would be applied to the FLA problems where various conflicting performance measures are considered. The procedure requires that conflicting performance measures classified as inputs to be minimized, or outputs to be maximized. Solving an MOP problem generates diverse alternative FLA schemes along with multi-objective values. DEA evaluates these schemes to generate a relative efficiency score for each scheme. Then, using stratification DEA, all of these FLA schemes are stratified into several levels, from the most efficient to the most inefficient levels. A case study is presented to demonstrate the effectiveness and efficiency of the proposed integrating method. We observe that the combined approach in this paper performs well and would provide many insights to academians as well as practitioners and researchers.
Subjects: 
Facility location-allocation
Data envelopment analysis
Multi-objective programming
Performance measures
Relative efficiency score
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.