Coronavirus Disease 2019 (COVID-19) Update
Due to heightened concerns regarding the outbreak of COVID-19, we are adding more instructor-led online training courses as an alternative to classroom courses.
Prerequisites
MATLAB Fundamentals . Knowledge of linear algebra and multivariate calculus is helpful.
This program has been approved by GARP and qualifies for 7 GARP CPD credit hours. If you are a Certified FRM or ERP, please record this activity in your credit tracker at http://www.garp.org/cpd.
Optimization Techniques in MATLAB
This one-day course introduces applied optimization in the MATLAB® environment, focusing on using Optimization Toolbox™ and Global Optimization Toolbox. Topics include:
- Running optimization problems in MATLAB
- Specifying objective functions and constraints
- Choosing solvers and improving performance
- Global and multiobjective optimization
Optimization Techniques in MATLAB
Prerequisites
MATLAB Fundamentals . Knowledge of linear algebra and multivariate calculus is helpful.
This program has been approved by GARP and qualifies for 7 GARP CPD credit hours. If you are a Certified FRM or ERP, please record this activity in your credit tracker at http://www.garp.org/cpd.
| Day 1 of 1 | |
|---|---|
| Running an Optimization Problem | Objective: Understand the basic structure and process of solving optimization problems effectively. Use interactive tools to define and solve optimization problems.
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| Specifying Objective Functions and Constraints | Objective: Write an optimization problem. Use problem-based workflow to arrive at a solution.
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| Choosing a Solver and Improving Performance | Objective: Select an appropriate solver and algorithm by considering the type of optimization problem to be solved. Interpret the output from the solver and diagnose the progress of an optimization.
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| Global and Multiobjective Optimization | Objective: Use Global Optimization Toolbox functionality to solve problems where classical algorithms fail or work inefficiently. Solve problems with many objectives.
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