Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEEM.2009.5373152
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dc.titleOptimizing wheat storage and transportation system using a mixed integer programming model and genetic algorithm: A case study
dc.contributor.authorFarahani, R.Z.
dc.contributor.authorAsgari, N.
dc.contributor.authorHojabri, H.
dc.contributor.authorJaafari, A.A.
dc.date.accessioned2014-04-23T08:16:56Z
dc.date.available2014-04-23T08:16:56Z
dc.date.issued2009
dc.identifier.citationFarahani, R.Z., Asgari, N., Hojabri, H., Jaafari, A.A. (2009). Optimizing wheat storage and transportation system using a mixed integer programming model and genetic algorithm: A case study. IEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management : 2109-2113. ScholarBank@NUS Repository. https://doi.org/10.1109/IEEM.2009.5373152
dc.identifier.isbn9781424448708
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/50795
dc.description.abstractThe investigated case is a vast country with a variety of climates. Due to this diversity in climate and therefore different farming conditions in different areas of the country, wheat is produced at different times of year all over the country. Therefore, wheat production rate is not constant during year all around the country. Lack of balance between wheat production and consumption in different provinces during different periods necessitates storage and transportation of wheat. In this paper, we intend to find the answer to the following question: "How much wheat in each month of year must be transported from each province to other provinces?" A mixed integer programming (MIP) model is developed for the problem and a genetic algorithm (GA) is designed because optimization solvers cannot solve the real-size problem in a reasonable time. To show efficiency, GA results are compared with those of LINGO 8.00 for randomly generated small-sized test problems. ©2009 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/IEEM.2009.5373152
dc.sourceScopus
dc.subjectGenetic algorithm
dc.subjectInventory
dc.subjectMixed integer programming
dc.subjectTransportation
dc.typeConference Paper
dc.contributor.departmentCIVIL ENGINEERING
dc.contributor.departmentCENTRE FOR MARITIME STUDIES
dc.description.doi10.1109/IEEM.2009.5373152
dc.description.sourcetitleIEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management
dc.description.page2109-2113
dc.identifier.isiut000280236601176
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