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Robust Shortest Paths under Uncertainty Using Conditional Value-at-Risk
(Oklahoma State University, 2011-12-01)
Finding a shortest path in a network is a classical problem in discrete optimization. The systems underlying the network models are subjects to a variety of sources of uncertainty. The purpose of this thesis is to model ...
Accelerating convergence of leapfrogging optimization - Applications to nonlinear process modeling and nonlinear model predictive control
(2014-07)
Conventionally used optimization methods in chemical engineering applications such as linear programming (LP), Levenberg-Marquardt and sequential quadratic programming (SQP) handle nonlinear objective function (OF) surfaces ...
Approach to Modeling and Optimization of Integrated Renewable Energy System (Ires)
(Oklahoma State University, 2013-12-01)
The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources using MATLAB programming. IRES is an effective and a viable ...