期刊
IEEE ACCESS
卷 8, 期 -, 页码 46288-46306出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2979259
关键词
Carbon emissions; carbon trading; green location-routing problem; robust optimization
资金
- National Natural Science Foundation of China [71702015]
- National Social Science Foundation of China [17BJL091]
- National key Research and Development Program on Intergovernmental Science and Technology Innovation Cooperation Research Project [2018YFE0196500]
- China Postdoctoral Science Foundation [2017M611810]
- Fundamental Science and Frontier Technology Research Project of Chongqing [cstc2017jcyjAX0130]
- Humanities and Social Sciences Research Program of the Chongqing Education Commission of China [18SKGH063]
- Research Platform Open Project of the CTBU [KFJJ2018079]
Taking carbon emissions into account in decision-making on distribution network operations contributes to achieving the goal of promoting energy conservation and emissions reduction. The focus of this paper is to research multicapacity hierarchical location-routing robust optimization in distribution network design under carbon trading policies. First, this problem is described as a mixed integer nonlinear programming model. Then, based on strong duality theory, the nonlinear model is transformed into a linear robust equivalent model. Finally, GUROBI software is used for numerical calculation and analysis. The results suggest the following: carbon trading policies have a carbon abatement effect; with a decrease in the carbon emissions cap and an increase in carbon trading prices, carbon emissions undergo a ladder-like downward trend; uncertain fluctuations in freight units will influence the optimal decision-making patterns of enterprises; and making more vehicles available will reduce carbon emissions. The government should set a reasonable carbon emissions cap according to market conditions. Enterprises could adopt robust control parameters on the basis of their decision-making preferences and consider the impact of carbon trading policy in formulating and adjusting an optimal decision-making scheme.
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