Optimization Toolbox

Optimization ToolboxDeveloper(s)| MathWorks

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Stable release|

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Operating system| Cross-platform[1]
Type| List of optimization software
License| Proprietary
Website| Optimization Toolbox

Optimization Toolbox is an optimization software package developed by MathWorks. It is an add-on product to MATLAB, and provides a library of solvers that can be used from the MATLAB environment. The toolbox was first released for MATLAB in 1990.

## Contents

* 1 Optimization algorithms
* 2 Applications
* 2.1 Engineering Optimization
* 2.2 Parameter Estimation
* 2.3 Computational Finance
* 2.4 Utilities and Energy
* 3 See also
* 4 References
* 5 Further reading

## Optimization algorithms

Optimization Toolbox has algorithms for:

* Linear programming
* Mixed-integer linear programming
* Quadratic programming
* Nonlinear programming
* Linear least squares
* Nonlinear least squares
* Nonlinear equation solving
* Multi-objective optimization

## Applications

### Engineering Optimization

Optimization Toolbox solvers are used for engineering applications in MATLAB, such as optimal control and optimal mechanical designs.[2][3]

### Parameter Estimation

Optimization can help with fitting a model to data, where the goal is to identify the model parameters that minimize the difference between simulated and experimental data. Common parameter estimation problems that are solved with Optimization Toolbox include estimating material parameters and estimating coefficients of ordinary differential equations.[4][5]

### Computational Finance

Portfolio optimization, cashflow matching, and other computational finance problems are solved with Optimization Toolbox.[6]

### Utilities and Energy

Optimization Toolbox solvers are used for security constrained optimal power flow and power systems analysis.[7]

## See also

* Mathematical optimization

## References

1. ↑ MathWorks - Optimization Toolbox - Requirements
2. ↑ Dragain, Andreas (2009). "Comparative Study of Numerical Methods for Optimal Control of a Biomechanical System". Chalmers University of Technology. http://publications.lib.chalmers.se/records/fulltext/134033.pdf.
3. ↑ Rao, Singiresu (2009). Engineering Optimization: Theory and Practice. Hoboken, New Jersey: John Wiley & Sons. p. 36. ISBN 978-0-470-18352-6. https://archive.org/details/engineeringoptim00raos_638.
4. ↑ Banks, H.T. (2013). "Material parameter estimation and hypothesis testing on a 1D viscoelastic stenosis model: Methodology". Journal of Inverse and Ill-Posed Problems 21 (1): 25–57. doi:10.1515/jip-2012-0081. http://www.lib.ncsu.edu/resolver/1840.4/8209.
5. ↑ Collins Licata, A. (2001). "A Physiologically Based Pharmacokinetic Model for Methyl tert-Butyl Ether in Humans: Implementing Sensitivity and Variability Analyses". Toxicological Sciences 62 (2): 191–204. doi:10.1093/toxsci/62.2.191. PMID 11452131.
6. ↑ Pachamanova, D. (2010). Simulation and Optimization in Finance + Web Site. Hoboken, New Jersey: John Wiley & Sons. ISBN 978-0-470-37189-3.
7. ↑ Cartina, G. (2007). "Power System Analysis using MATLAB Toolboxes". 6th International Conference on Electromechanical and Power Systems: 305–308.

## Further reading

* Venkataraman, P. (2009). "Optimization Toolbox from Matlab". Applied Optimization with MATLAB Programming (2nd ed.). Hoboken: John Wiley & Sons. pp. 469–488. ISBN 978-0-470-08488-5. https://books.google.com/books?id=kKWs51HLLA8C&pg=PA469.

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