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.
Highlights
Productivity measurement and efficiency in particular is a common term among the discipline of production economics
In the past decades there have been advances in Integer Programming (IP); one of which is Mixed Logical Linear Programming (MLLP) or Mixed Integer Linear (MILP) Programming models, where binary variables provide information regarding the installation of a plant or the selection of a route or a procedure, depending on the nature of the model (Hooker and Osorio 1999)
Using Data Envelopment Analysis (DEA) technique the efficiency is extracted for each DMU under examination
Summary
Productivity measurement and efficiency in particular is a common term among the discipline of production economics. If more than one sites are selected a possible approach is to add a single sourcing constraint which will select a single facility that reduces greatly the overall cost, but it may cause the problem to become infeasible In this case, other methodologies must be employed in order to provide solution to the problem. The models that are used in order to design supply chain network, use single sourcing constraint in order to reduce the number of facilities by imposing the model to select one facility to accommodate a cluster of demand zones. This constraint is hard and often leads to infeasibility. An approach that is integrating DEA technique in the selection of solutions, providing a Multi-Objective Programming model, as solutions are subjected to constraints to the problem, and to the “efficiency cuts” that are posed by B&E approach, has not yet been proposed in the supply chain literature
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