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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/9042
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dc.contributor.advisorMahalec, Vladimiren_US
dc.contributor.authorKulkarni, Shefalien_US
dc.date.accessioned2014-06-18T16:45:16Z-
dc.date.available2014-06-18T16:45:16Z-
dc.date.created2011-05-25en_US
dc.date.issued2009-08en_US
dc.identifier.otheropendissertations/4200en_US
dc.identifier.other5218en_US
dc.identifier.other2031059en_US
dc.identifier.urihttp://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.subjectComputational Engineeringen_US
dc.subjectComputational Engineeringen_US
dc.titleOptimal Multi-Time Period Gasoline Blendingen_US
dc.typethesisen_US
dc.contributor.departmentComputational Engineering and Scienceen_US
dc.description.degreeMaster of Applied Science (MASc)en_US
Appears in Collections:Open Access Dissertations and Theses

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