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Optimization of Supply Chain Systems with Price Elasticity of Demand
Date
2011-09-01
Author
Kaplan, Ugur
TÜRKAY, METİN
Karasözen, Bülent
Biegler, Lorenz T.
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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A centralized multiechelon, multiproduct supply chain network is presented in a multiperiod setting with products that show varying demand against price. An important consideration in such complex supply chains is to maintain system performance at high levels for varying demands that may be sensitive to product price. To examine the price-centric behavior of the customers, the concept of price elasticity of demand is addressed. The proposed approach includes many realistic features of typical supply chain systems such as production planning and scheduling, inventory management, transportation delay, transportation cost, and transportation limits. In addition, the proposed system can be extended to meet unsatisfied demand in future periods by backordering. Effects of the elasticity in price demand in production and inventory decisions are also examined. The supply chain model is formulated as a convex mixed-integer nonlinear programming problem. Reformulations are presented to make the problem tractable. The differential equations are reformulated as difference equations, and unbounded derivatives in the nonlinear objective function are handled with an approximation, with guaranteed bounds on the loss of optimality. The approach is illustrated on a multiechelon, multiproduct supply chain network.
Subject Keywords
Mixed-integer nonlinear programming
,
Supply chain management
,
Smoothing
,
Price elasticity of demand
URI
https://hdl.handle.net/11511/30709
Journal
INFORMS JOURNAL ON COMPUTING
DOI
https://doi.org/10.1287/ijoc.1100.0421
Collections
Graduate School of Applied Mathematics, Article
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U. Kaplan, M. TÜRKAY, B. Karasözen, and L. T. Biegler, “Optimization of Supply Chain Systems with Price Elasticity of Demand,”
INFORMS JOURNAL ON COMPUTING
, pp. 557–568, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/30709.