Vorlesen

Optimizing an emission allowance trading scheme for local governments: A Stackelberg game model and hybrid algorithm

Wirtschaftsuniversität Wien, Departments 2 Room 0.3817:00 - 18:30

Art Vortrag/Diskussion
Vortragende/rDr. Linda Zhang
Veranstalter Forschungsinstitut Supply Chain Management
Kontakt isabel.uko@wu.ac.at

Dr. Linda Zhang

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.



zurück zur Übersicht