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In this webinar, you will learn how MATLAB can be used to solve optimization problems. An example quadratic optimization problem is given, and the symbolic math tools in MATLAB are used to move from the governing equations to an objective function that can be evaluated. Different methods are used to obtain a solution, and the trade-offs between development time and solution time are demonstrated. Finally, the example is scaled up to the full, large-scale problem.
Highlights include:
Identifying quadratic problems during the optimization process
Formulating an optimization problem in MATLAB
Speeding up gradient calculations using Symbolic Math Toolbox™
Scaling up to a large-scale, constrained quadratic programming problem
