Modelling the semi-additive production technology in DEA

Mojtaba Ghiyasi and Wade D. Cook

Omega, 2021, vol. 103, issue C

Abstract: The semi-additive production technology allows for the aggregation of production units in the process of efficiency analysis using data envelopment analysis (DEA). This means that one must consider not only the full set of decision-making units (DMUs), but as well the entire power set, that is the set of all aggregations of the set of DMUs. Specifically, for n DMUs the number of variables involved is 2n, hence requiring one to solve a set of linear programming problems, each of size O(2n). In a big data sense, such a problem becomes prohibitive as n increases. The current paper proposes a new model that significantly decreases the computational complexity of models based on the semi-additive production technology. We show that the proposed semi-additive methodology allows the number of variables to be decreases from2nto n, and the complexity of the algorithm to be reduced from O(2n)to O(n). Three numerical and graphical examples are presented to illustrate the methodology.

Keywords: DEA; Semi-additive production technology; Computational complexity; Power set (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305048320307398
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:103:y:2021:i:c:s0305048320307398

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.omega.2020.102385

Access Statistics for this article

Omega is currently edited by B. Lev

More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().