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Integration optimization of biomass supply based on logit model

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DOI: 10.23977/agrfem.2019.21003 | Downloads: 13 | Views: 2226


Wang Peng 1


1 School of Economics and Management, Dalian University, No.10, Xuefu Avenue, Economic & Technical Development Zone, Dalian, Liaoning,The People's Republic of China(PRC)

Corresponding Author

Wang Peng


Considering the choice preference of farmers, this paper introduced a Logit-based discrete econometric analysis model to study the influence of straw purchase price, cost and government subsidy on the biomass supply choice behavior off armers. On this basis, this study applied the Stackelberg game model to analyze the decision-making among different stakeholders in the biomass supply chain, such as biorefinery, collection stations and farmers, and determined the optimal purchase price of biomass and the service radius of collection stations. Finally, it used a numerical example to verify the effectiveness of the optimal decision-making model. The research shows that the choice of farmer's supply mode is related to their sensitivity to utility; government subsidies can not only improve the enthusiasm of farmers to send straw directly to the biorefinery, but also improve the interests of the biorefinery and collection stations to different degrees.


biomass; Logit model; pricing decision; service radius; Stackelberg game


Wang Peng, Integration optimization of biomass supply based on logit model. Agricultural & Forestry Economics and Management (2019) Vol. 2: 15-18. DOI:


[1] Mosahar Tarimoradi, (2015) Evolutionary fuzzy intelligent system for multi-objective supply chain network designs: an agent-based optimization state of the art,  Journal of Intelligent Manufacturing, 5,1551-1579
[2] Hernan Chavez. (2017) Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain, Energies, 5, 356-374.
[3] Zhexuan Liu. (2015) A study of the LCA based biofuel supply chain multi-objective optimization model with multi-conversion paths in China. Applied Energy, 3, 105-112.

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