DocumentCode
617857
Title
Multi-objective Stackelberg game between a regulating authority and a mining company: A case study in environmental economics
Author
Sinha, Aloka ; Malo, Pedro ; Frantsev, Anton ; Deb, Kaushik
Author_Institution
Sch. of Bus., Dept. of Inf. & Service Econ., Aalto Univ., Helsinki, Finland
fYear
2013
fDate
20-23 June 2013
Firstpage
478
Lastpage
485
Abstract
Bilevel programming problems are often found in practice. In this paper, we handle one such bilevel application problem from the domain of environmental economics. The problem is a Stakelberg game with multiple objectives at the upper level, and a single objective at the lower level. The leader in this case is the regulating authority, and it tries to maximize its total tax revenue over multiple periods while trying to minimize the environmental damages caused by a mining company. The follower is the mining company whose sole objective is to maximize its total profit over multiple periods under the limitations set by the leader. The solution to the model contains the optimal taxation and extraction decisions to be made by the players in each of the time periods. We construct a simplistic model for the Stackelberg game and provide an analytical solution to the problem. Thereafter, the model is extended to incorporate realism and is solved using a bilevel evolutionary algorithm capable of handling multiple objectives.
Keywords
decision making; environmental economics; game theory; government; mathematical programming; mining industry; profitability; taxation; analytical solution; bilevel evolutionary algorithm; bilevel programming problems; environmental damage minimization; environmental economics; lower level; mining company; multiobjective Stackelberg game; multiple objectives; optimal extraction decision making; optimal taxation decision making; regulating authority; time periods; total profit maximization; total tax revenue maximization; upper level; Companies; Cost function; Games; Gold; Government; Pollution; Stackelberg games; bilevel programming; environmental economics; genetic algorithm; multi-criteria decision making;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location
Cancun
Print_ISBN
978-1-4799-0453-2
Electronic_ISBN
978-1-4799-0452-5
Type
conf
DOI
10.1109/CEC.2013.6557607
Filename
6557607
Link To Document