Optimizing an emission allowance trading scheme for local governments: A Stackelberg game model and hybrid algorithm
We investigate a policy-making problem for a local government to implement a market driven emission allowance trading scheme by considering the interactive production decisions of firms in its administrative region. The government sets the emission reduction target of the region and allocates tradable initial allowances to firms, and firms plan their production according to their allowances on hand. In accordance with the characteristics of the problem, we formulate a Stackelberg game model to analyze the decisions of the government and firms aiming to maximize the social welfare of the region and minimize the overall cost of each firm. In view of the non-concavity and discreteness of the decision model for the government, we develop a hybrid algorithm to solve the game model efficiently. This algorithm consists of a polynomial time dynamic programming, binary search, and genetic algorithm. Results reveal that i) the Stackelberg game model greatly supports local governments' policy-making on the market-driven emission allowance trading scheme, and that ii) the social welfare is a great metric for policy-making decisions on environmental regulations.
Dr. Linda Zhang
Forschungsinstitut Supply Chain Management
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