Issue |
RAIRO-Oper. Res.
Volume 58, Number 4, July-August 2024
|
|
---|---|---|
Page(s) | 3391 - 3416 | |
DOI | https://doi.org/10.1051/ro/2024117 | |
Published online | 27 August 2024 |
Multi-choice conic goal programming model-based network data envelopment analysis
1
Kütahya Dumlupınar University, Faculty of Engineering, Department of Industrial Engineering, Kütahya, Turkey
2
Aksaray University, Faculty of Engineering, Department of Industrial Engineering, Aksaray, Turkey
3
Eski¸sehir Osmangazi University, Faculty of Engineering, Department of Industrial Engineering, Eski¸sehir, Turkey
* Corresponding author: derya.deliktas@dpu.edu.tr; derya.deliktas@outlook.com
Received:
24
November
2023
Accepted:
22
May
2024
In multi-stage processes, classical Data Envelopment Analysis (DEA) acts like a black box and measures the efficiency of decision-making units (DMUs) without considering the internal structure of the system. Unlike classical DEA, recent studies have shown that the overall system efficiency scores are more meaningful if researched using the Network DEA (NDEA) methodology. NDEA performs simultaneous efficiency evaluations of sub-processes and the entire system. Recently, the composition method integrated with multi-objective programming (MOP) has been preferred by many authors to alleviate the drawbacks of earlier methods such as decomposition, slack-based measure (SBM) and the system-centric approach. This study proposes a novel approach incorporating Multi-Choice Conic Goal Programming into the NDEA (MCCGP-NDEA). It provides a more accurate representation of the Pareto front by revealing potential Pareto optimal solutions which are overlooked by the composition methods. Due to its ability to modify stage weights based on the decision makers’ (DMs) preferences, it is likely to gather more samples from the Pareto surface. Computational results on available benchmark problems confirm that the proposed MCCGP-NDEA is a viable alternative to existing methods.
Key words: Data envelopment analysis / network DEA / multi-choice conic goal programming / multi-objective programming
© The authors. Published by EDP Sciences, ROADEF, SMAI 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.