Optimal Choice of Enterprise's Production Strategy under Constraints of Carbon Quota

After analyzing the enterprise’s production strategy under the constraints of carbon quota, this paper proposes new mathematical models aiming for the optimal choice of enterprise’s production strategy under the monopoly and competitive environments respectively. Combining the neural network optimization theory, then the methods of Nonlinear Programming and Nash Equilibrium in Static Games are used to solve the models to obtain the enterprise’s equilibrium quantity, the optimal carbon emission, and the profit of unit product in the low carbon technology. The study found that: under a monopoly environment, enterprises choose technology innovation strategy; under a competitive environment, enterprises use carbon trading strategies whenever carbon trading prices are low or high; however, there is no pure strategy Nash equilibrium when carbon trading prices are in the middle, in this case enterprises prefer to use the production strategies different from the competitor.

[1]  Terry Barker,et al.  A UK carbon/energy tax: The macroeconomics effects , 1993 .

[2]  H. Welsch,et al.  Energy-Capital-Labor Substitution and the Economic Effects of CO2 Abatement: Evidence for Germany , 2000 .

[3]  Jinde Cao,et al.  Absolute exponential stability of recurrent neural networks with Lipschitz-continuous activation functions and time delays , 2004, Neural Networks.

[4]  Ravi Subramanian,et al.  Compliance Strategies Under Permits for Emissions , 2007 .

[5]  Imre Dobos,et al.  Tradable permits and production-inventory strategies of the firm , 2007 .

[6]  Roger Tagg,et al.  Intelligent Concepts for the Management of Information in Workflow Systems , 2009, Int. J. Comput. Intell. Syst..

[7]  Wang Zheng,et al.  Abatement Effect of Carbon Tax and Its Impacts on Economy in China , 2010 .

[8]  Peter E. Earl,et al.  Economic perspectives on the development of complex products for increasingly demanding customers , 2010 .

[9]  Oscar Camacho Nieto,et al.  Pollutants Time-Series Prediction using the Gamma Classifier , 2011, Int. J. Comput. Intell. Syst..

[10]  Adisa Azapagic,et al.  Carbon trading: Current schemes and future developments , 2011 .

[11]  Liu Yi-wen,et al.  General Equilibrium Analysis of Carbon Tax under Different Tax Return Mechanisms , 2011 .

[12]  Daren Yu,et al.  Fuzzy Mutual Information Based min-Redundancy and Max-Relevance Heterogeneous Feature Selection , 2011, Int. J. Comput. Intell. Syst..

[13]  S. Wong The influence of green product competitiveness on the success of green product innovation , 2012 .

[14]  Manoj Kumar Tiwari,et al.  A decision framework for the analysis of green supply chain contracts: An evolutionary game approach , 2012, Expert Syst. Appl..

[15]  A. Ramudhin,et al.  Design of sustainable supply chains under the emission trading scheme , 2012 .

[16]  Dengpan Ye,et al.  Uncertainty Multi-source Information Fusion for Intelligent Flood Risk Analysis Based on Random Set Theory , 2012, Int. J. Comput. Intell. Syst..

[17]  Michael W. Toffel,et al.  Engaging Supply Chains in Climate Change , 2012, Manuf. Serv. Oper. Manag..

[18]  Sean X. Zhou,et al.  Optimal Production Planning with Emissions Trading , 2013, Oper. Res..

[19]  Yue Zheng,et al.  Optimization Decision of Supplier Selection in Green Procurement under the Mode of Low Carbon Economy , 2015, Int. J. Comput. Intell. Syst..

[20]  Michael J. Todd,et al.  Computation, Multiplicity, and Comparative Statics of Cournot Equilibria in Integers , 2016, Math. Oper. Res..

[21]  Guillaume Carlier,et al.  Optimal Transport and Cournot-Nash Equilibria , 2012, Math. Oper. Res..

[22]  Osman Y. Özaltın,et al.  Note on Cournot Competition Under Yield Uncertainty , 2017, Manuf. Serv. Oper. Manag..