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

Vortrag des Forschungs­in­sti­tuts Supply Chain Manage­ment
22. Mai 2017
17:00 Uhr
Wirt­schafts­uni­ver­sität Wien, Welt­han­dels­platz 1, 1020 Wien
Gebäude D2, Ground Floor, Room 0.38

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.

Vortra­gende: Dr. Linda Zhang