Data envelopment analysis approaches for two-level production and distribution planning problems
Ichiro Nishizaki,
Tomohiro Hayashida,
Shinya Sekizaki and
Junya Okabe
European Journal of Operational Research, 2022, vol. 300, issue 1, 255-268
Abstract:
In this paper, we focus on a two-level production and distribution planning problem in the field of supply chain management, and examine the situations where the leader does not fully know the manufacturing technologies of the follower. In such a situation, the parameters representing the manufacturing technologies cannot be explicitly used to formulate the follower’s production planning problem. To overcome this difficulty, we propose formulations that implicitly express manufacturing technologies by using the input-output data observed from the production activities of the follower, incorporating the idea of data envelopment analysis (DEA). Assuming that the follower has multiple production facilities, we consider two possibilities of the observable input-output data and formulate two corresponding production planning problems; firstly, that only the input-output data aggregated for all the production facilities can be observed collectively, and secondly, that the input-output data for each of the production facilities can be observed separately. To clarify the validity of these DEA approaches, we compare them with the conventional formulation with technological coefficients using a numerical example.
Keywords: Data envelopment analysis; Two-level programming problem; Production and distribution planning problems (search for similar items in EconPapers)
Date: 2022
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/S0377221721006573
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:ejores:v:300:y:2022:i:1:p:255-268
DOI: 10.1016/j.ejor.2021.07.047
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().