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http://hdl.handle.net/11375/9042
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DC Field | Value | Language |
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dc.contributor.advisor | Mahalec, Vladimir | en_US |
dc.contributor.author | Kulkarni, Shefali | en_US |
dc.date.accessioned | 2014-06-18T16:45:16Z | - |
dc.date.available | 2014-06-18T16:45:16Z | - |
dc.date.created | 2011-05-25 | en_US |
dc.date.issued | 2009-08 | en_US |
dc.identifier.other | opendissertations/4200 | en_US |
dc.identifier.other | 5218 | en_US |
dc.identifier.other | 2031059 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/9042 | - |
dc.description.abstract | <p>Multi Time period Gasoline blending is an example of multipurpose production system that is designed to produce multiple products by switching from one product to another. Various factors such as demand for gasoline, availability of supply component, and blend recipes vary with time. Task of the gasoline blender is to decide how much of each product to produce at what point in time (lot sizing) and what should be the blend recipe in order to minimize overall cost (optimize the blend recipe) . The production plans need to account for set-up times between blends and to minimize switching between different product blends. Traditional optimization techniques provide a single optimal solution. This research is using evolutionary optimization algorithm called differential evolution to identify multiple solutions t hat all have the same total cost but offer the blend planner multiple choices in terms of how much of a given product to blend at what point in time.</p> | en_US |
dc.subject | Computational Engineering | en_US |
dc.subject | Computational Engineering | en_US |
dc.title | Optimal Multi-Time Period Gasoline Blending | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Computational Engineering and Science | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 28.5 MB | Adobe PDF | View/Open |
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