Optimization models for biorefinery supply chain network design under uncertainty

dc.contributor.author Kazemzadeh, Narges
dc.contributor.author Hu, Guiping
dc.contributor.department Department of Industrial and Manufacturing Systems Engineering
dc.date 2018-02-18T07:47:54.000
dc.date.accessioned 2020-06-30T04:47:40Z
dc.date.available 2020-06-30T04:47:40Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2013
dc.date.issued 2013-01-01
dc.description.abstract <p>Biofuel industry has attracted much attention due to its potential to reduce dependency on fossil fuels and contribute to the renewable energy. The high levels of uncertainty in feedstock yield, market prices, production costs, and many other parameters are among the major challenges in this industry. This challenge has created an ongoing interest on studies considering different aspects of uncertainty in investment decisions of the biofuel industry. This study aims to determine the optimal design of supply chain for biofuel refineries in order to maximize annual profit considering uncertainties in fuel market price, feedstock yield, and logistic costs. In order to deal with the stochastic nature of parameters in the biofuel supply chain, we develop two-stage stochastic programming models in which Conditional Value at Risk (CVaR) is utilized as a risk measure to control the amount of shortage in demand zones. Two different approaches including the expected value and CVaR of the profit are considered as the objective function. We apply these models and compare the results for a case study of the biomass supply chain network in the state of Iowa to demonstrate the applicability and efficiency of the presented models.</p>
dc.description.comments <p>This is an article from <em>Journal of Renewable and Sustainable Energy</em> 5 (2013): 053125, doi:<a href="http://dx.doi.org/10.1063/1.4822255">10.1063/1.4822255</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/imse_pubs/106/
dc.identifier.articleid 1106
dc.identifier.contextkey 9937507
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath imse_pubs/106
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/44393
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/imse_pubs/106/2013_Hu_OptimizationModels.pdf|||Fri Jan 14 18:24:21 UTC 2022
dc.source.uri 10.1063/1.4822255
dc.subject.disciplines Industrial Engineering
dc.subject.disciplines Systems Engineering
dc.title Optimization models for biorefinery supply chain network design under uncertainty
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication a9a9fb1b-4a43-4d73-9db6-8f93f1551c44
relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
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