随机产出下基于CDM基准线选择的多企业碳减排博弈

工业工程 ›› 2012, Vol. 15 ›› Issue (3): 1-6.

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随机产出下基于CDM基准线选择的多企业碳减排博弈

天津大学管理与经济学部, 天津 300072

出版日期:2012-06-30 发布日期:2012-07-21
作者简介:赵道致（1956-），男，江苏省人，教授，博士，主要研究方向为运营管理、物流与供应链管理、制造系统优化、工业工程与应用、项目管理等.
基金资助:
国家自然科学基金资助项目(70802044,71072155)

A Game Approach to Carbon Emission Reduction for Multi-Enterprises Based on CDM Baseline Selection under Stochastic Output

College of Management and Economics, Tianjin University, Tianjin 300072, China

Online:2012-06-30 Published:2012-07-21

摘要/Abstract

摘要： 着眼于具有随机产出特点的行业中多家企业实施CDM项目的情景,研究行业中多企业碳排放博弈问题。详细比较了在相同基准线下,不同数量的企业实施CDM项目后的利润、成本、均衡产量和碳减排量; 又比较了在不同基准线下,相同数量的企业实施CDM项目后的利润、成本、均衡产量和碳减排量。指出在面临不同基准线时,企业既要考虑利润又要考虑政府的偏好;给出了企业的决策建议,帮助企业选择正确的基准线,从而在得到政府允许的前提下获得最大利润。

关键词: 低碳经济, 清洁发展机制(CDM)基准线, 博弈论

Abstract: The problem of carbon emission reduction is discussed in this paper in the scenario of clean development mechanism (CDM) project adopted by multiple enterprises with stochastic output. A game model is developed to describe the problem. With the model, under the same CDM baseline, the profit, cost, equilibrium output, and carbon emission reduction are analyzed with different number of enterprises that adopt the CDM project. The same analysis is also done under different CDM baselines. Results show that, when there are different CDM baselines, an enterprise should take both its profit and the government preference into consideration. Also, it suggests that an enterprise should select a right baseline so as to obtain the government approval and get the maximal profit.

Key words: lowcarbon economy, clean development mechanism (CDM) baseline, game theory

赵道致, 高帅, 何龙飞. 随机产出下基于CDM基准线选择的多企业碳减排博弈[J]. 工业工程, 2012, 15(3): 1-6.

Zhao Daozhi, Gao Shuai, He Longfei. A Game Approach to Carbon Emission Reduction for Multi-Enterprises Based on CDM Baseline Selection under Stochastic Output[J]. Industrial Engineering Journal , 2012, 15(3): 1-6.

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随机产出下基于CDM基准线选择的多企业碳减排博弈

A Game Approach to Carbon Emission Reduction for Multi-Enterprises Based on CDM Baseline Selection under Stochastic Output

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