Computational Approach to Function Minimization and Optimization with Constraints Sharma, Rohan
dc.contributor.department Aerospace Engineering 2018-02-14T09:58:38.000 2020-07-07T05:10:28Z 2020-07-07T05:10:28Z 2014-04-15
dc.description.abstract <p>This research conducted analyzes function minimization and optimization in the MATLAB programming environment. Different methods are examined and an assessment is made on which tool to utilize given an arbitrary function. This function can be of many types such as quadratic, linear, least squares, smooth nonlinear differential equation, or non-smooth differential equation. The constraints can be of many types as well such as bound, linear, general smooth, and discrete. It is important to note that optimization can also be done on functions which are not bound by constraints. Optimization methods are assessed under two categories, accuracy and computation time, in an attempt to determine the best optimizer to be used given a set type of function. In addition, this research focuses on the function minimization process of typical optimization testing functions. With system optimization becoming a growing field, this research has impactful implications on its computational approach and improving efficiencies of such processes.</p>
dc.identifier archive/
dc.identifier.articleid 1029
dc.identifier.contextkey 5914589
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath undergradresearch_symposium/2014/presentations/30
dc.source.bitstream archive/|||Fri Jan 14 23:26:54 UTC 2022
dc.subject.disciplines Systems Engineering and Multidisciplinary Design Optimization
dc.title Computational Approach to Function Minimization and Optimization with Constraints
dc.type event
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication 047b23ca-7bd7-4194-b084-c4181d33d95d Aerospace Engineering and Physics
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