Transcription of Solving Optimization Problems with MATLAB
{{id}} {{{paragraph}}}
1 2018 The MathWorks, Optimization Problems with MATLAB2 Introduction Least-squares minimization Nonlinear Optimization mixed -integer programming Global optimizationTopics3 Optimization ProblemsMinimize RiskMaximize ProfitsMaximize Fuel Efficiency4 Design ProcessInitial Design VariablesSystemModify Design VariablesOptimal DesignObjectivesmet?NoYes5 Manually (trial-and-error or iteratively)Why use Optimization ?Initial Guess6 Automatically (using optimizationtechniques)Initial GuessWhy use Optimization ?7 Why use Optimization ? Finding better (optimal) designs and decisions Faster design and decision evaluations Automate routine decisions Useful for trade-off analysis Non-intuitive designs may be foundAntenna Design Using Genetic Introduction Least-squares minimization Nonlinear Optimization mixed -integer programming Global optimizationTopics9 Curve Fitting DemoGiven some data:Fit a curve of the form:teccty 21)(t = [0.]
Mixed-Integer Programming Many things exist in discrete amounts: – Shares of stock – Number of cars a factory produces – Number of cows on a farm Often have binary decisions: – On/off – Buy/don’t buy Mixed-integer linear programming: – Solve optimization problem while enforcing that certain variables need to be integer
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
{{id}} {{{paragraph}}}