Optimal integration of third-parties in a coordinated supply chain management environment

A generic tactical model is developed considering third party price policies for the optimization of coordinated and centralized multi-product Supply Chains (SCs). To allow a more realistic assessment of these policies in each marketing situation, different price approximation models to estimate these policies are proposed, which are based on the demand elasticity theory, and result in different model implementations (LP, NLP, and MINLP). The consequences of using the proposed models on the SCs coordination, regarding not only their practical impact on the tactical decisions, but also the additional mathematical difficulties to be solved, are verified through a case study in which the coordination of a production–distribution SC and its energy generation SC is analyzed. The results show how the selection of the price approximation model affects the tactical decisions. The average price approximation leads to the worst decisions with a significant difference in the real total cost in comparison with the best piecewise approximation.

[1]  L. Puigjaner,et al.  Decentralized Manufacturing Supply Chains Coordination under Uncertain Competitiveness , 2015 .

[2]  Antonio Espuña Camarasa,et al.  Scenario-based price negotiations vs. game theory in the optimization of coordinated supply chains , 2015 .

[3]  Erbao Cao,et al.  Coordination of a supply chain with one manufacturer and multiple competing retailers under simultaneous demand and cost disruptions , 2013 .

[4]  Antonio Espuña,et al.  Application of Pricing Policies for Coordinated Management of Supply Chains , 2014 .

[5]  Carlos A. Méndez,et al.  Multi-period design and planning of closed-loop supply chains with uncertain supply and demand , 2014, Comput. Chem. Eng..

[6]  Z. K. Weng,et al.  Channel coordination and quantity discounts , 1995 .

[7]  Jeremy F. Shapiro,et al.  Challenges of strategic supply chain planning and modeling , 2004, Comput. Chem. Eng..

[8]  José Miguel Laínez,et al.  Flexible design‐planning of supply chain networks , 2009 .

[9]  James D. Gwartney Economics: Private and Public Choice , 1976 .

[10]  Christodoulos A. Floudas,et al.  GloMIQO: Global mixed-integer quadratic optimizer , 2012, Journal of Global Optimization.

[11]  Ana Paula F. D. Barbosa-Póvoa,et al.  The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure , 2009, Comput. Chem. Eng..

[12]  Antonio Espuña Camarasa,et al.  Tactical management for coordinated supply chains , 2014, Comput. Chem. Eng..

[13]  G. Guillén‐Gosálbez,et al.  Enhancing Corporate Value in the Optimal Design of Chemical Supply Chains , 2007 .

[14]  J.M. Laínez,et al.  Challenges and opportunities in enterprise-wide optimization in the pharmaceutical industry , 2012, Comput. Chem. Eng..

[15]  Ignacio E. Grossmann,et al.  Enterprise‐wide optimization: A new frontier in process systems engineering , 2005 .

[16]  Antonio Espuña Camarasa,et al.  Simultaneous optimization of process operations and financial decisions to enhance the integrated planning/scheduling of chemical supply chains , 2006, Comput. Chem. Eng..

[17]  Nilay Shah,et al.  Process industry supply chains: Advances and challenges , 2005, Comput. Chem. Eng..

[18]  Luis Puigjaner,et al.  Design of regional and sustainable bio-based networks for electricity generation using a multi-objective MILP approach , 2012 .

[19]  Marianthi G. Ierapetritou,et al.  Production planning and scheduling integration through augmented Lagrangian optimization , 2010, Comput. Chem. Eng..

[20]  Gintaras V. Reklaitis,et al.  Linking marketing and supply chain models for improved business strategic decision support , 2010, Comput. Chem. Eng..

[21]  Qinan Wang,et al.  Discount Pricing Policies and the Coordination of Decentralized Distribution Systems , 2005, Decis. Sci..

[22]  S. Viswanathan,et al.  Discount pricing decisions in distribution channels with price-sensitive demand , 2003, Eur. J. Oper. Res..

[23]  Marianthi G. Ierapetritou,et al.  Integrated production planning and scheduling optimization of multisite, multiproduct process industry , 2012, Comput. Chem. Eng..

[24]  C. Maravelias,et al.  An attainable region approach for production planning of multiproduct processes , 2007 .