Petridis, Konstantinos, Dey, Prasanta Kumar and Emrouznejad, Ali (2017). A branch and efficiency algorithm for the optimal design of supply chain networks. Annals of Operations Research, 253 (1), 545–571.
Abstract
Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.
Publication DOI: | https://doi.org/10.1007/s10479-016-2268-3 |
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Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences > Aston Business School > Aston India Foundation for Applied Research College of Business and Social Sciences > Aston Business School |
Additional Information: | © The Author(s) 2016. This article is published with open access at Springerlink.com |
Uncontrolled Keywords: | branch and bound,DEA,integer programming,mixed integer linear programming (MILP),supply chain management,General Decision Sciences,Management Science and Operations Research |
Publication ISSN: | 1572-9338 |
Last Modified: | 10 Dec 2024 18:45 |
Date Deposited: | 01 Sep 2016 08:20 |
Full Text Link: | |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) https://link.sp ... 0479-016-2268-3 (Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2017-06-01 |
Published Online Date: | 2016-08-02 |
Accepted Date: | 2016-06-26 |
Authors: |
Petridis, Konstantinos
Dey, Prasanta Kumar ( 0000-0002-9984-5374) Emrouznejad, Ali ( 0000-0001-8094-4244) |