A branch and efficiency algorithm for the optimal design of supply chain networks

Petridis, Konstantinos, Dey, Prasanta Kumar and Emrouznejad, Ali (2016). A branch and efficiency algorithm for the optimal design of supply chain networks. Annals of Operations Research, In pre ,

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
Divisions: Aston Business School > Operations & Information Management
Aston Business School > Aston India Foundation for Applied Research
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,Decision Sciences(all),Management Science and Operations Research
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2016-08-02
Published Online Date: 2016-08-02
Authors: Petridis, Konstantinos
Dey, Prasanta Kumar ( 0000-0002-9984-5374)
Emrouznejad, Ali ( 0000-0001-8094-4244)

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