Infrastructure deployment under uncertainties and competition: The biofuel industry case

•We optimize location of emerging facilities under competition and uncertainties.•The biofuel and food industry is used as the context for model development.•A Stackelberg–Nash game encompasses the biofuel vs. food industry, and farmers.•Equilibrium is derived via continuum approximation and functio...

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Bibliographic Details
Published in:Transportation research. Part B: methodological 2015-08, Vol.78, p.1-15
Main Authors: Wang, Xin, Lim, Michael K., Ouyang, Yanfeng
Format: Article
Language:English
Subjects:
Algorithms
Biofuel infrastructure deployment
Biomass
Competition
Continuum approximation
Facility disruption
Fuels
Infrastructure
Mathematical analysis
Mathematical models
Stackelberg–Nash competition
Uncertainty
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Summary:•We optimize location of emerging facilities under competition and uncertainties.•The biofuel and food industry is used as the context for model development.•A Stackelberg–Nash game encompasses the biofuel vs. food industry, and farmers.•Equilibrium is derived via continuum approximation and functional optimization.•Efficient algorithms are developed and applied to experiments and a case study. Technological paradigm shifts often come with a newly emerging industry that seeks a viable infrastructure deployment plan to compete against established competitors. Such phenomenon has been repeatedly seen in the field of transportation systems, such as those related to the booming bioenergy production, among others. We develop a game-theoretic modeling framework using a continuum approximation scheme to address the impacts of competition on the optimal infrastructure deployment. Furthermore, we extend the model to incorporate uncertainties in supply/demand and the risk of facility disruptions. Analytical properties of the optimal infrastructure system are obtained, based on which fast numerical solution algorithms are developed. Several hypothetical problem instances are used to illustrate the effectiveness of the proposed algorithms and to quantify the impacts of various system parameters. A large-scale biofuel industry case study for the U.S. Midwest is conducted to obtain additional managerial insights.
ISSN:0191-2615
1879-2367
DOI:10.1016/j.trb.2015.03.010