Overview
Engineers use optimization tools to automate finding the best design parameters while satisfying project requirements and to evaluate trade-offs among competing designs. Using these tools results in faster design iterations and allows evaluating a larger number of parameters and alternative designs compared with manual approaches.
We will show how to use apps and functions in Optimization Toolbox and Global Optimization Toolbox to define and solve design optimization problems. Optimization can be applied to design models that are either analytic or black-box including those built with machine learning and simulations. We will use examples from different engineering domains to demonstrate these capabilities.
Highlights
- Defining objectives, constraints and design variables
- Interactively creating and solving optimization problems with an app
- Choosing the best solver for your problem
- Setting options to improve results
- Using parallel computing to accelerate design studies
About the Presenters
Mary Fenelon is the product manager for the MATLAB optimization products. Before joining MathWorks, she managed the CPLEX Optimization Studio development team at IBM and developed early versions of the CPLEX mixed-integer programming solver. Mary earned a PhD in Operations Research at Stanford University.
Jason Rodgers is a senior application engineer at MathWorks. Prior to MathWorks, he spent five and a half years at Toyota R&D in the Model-Based Design group. He specialized in powertrain modeling and using model-based control, along with various optimization techniques to develop new powertrain systems. Jason earned a B.S.M.E. and an M.S.C. from the University of Michigan.
Peter Brady is an application engineer with MathWorks striving to accelerate our customer’s engineering and scientific computing workflows across maths, statistics, finance and machine learning. Prior to joining MathWorks, Peter worked in computational fluid and thermodynamics as well as high performance computing for a number of defence and civil contractors as well as a few universities. He has worked in fields as diverse as cavitation, wave/turbulence interactions, rainfall and runoff, nano-fluidics, HVAC and natural convection including scale out cloud simulation techniques. Peter holds doctorate in free surface computational fluid dynamics and a Bachelor of Civil Engineering both from the University of Technology Sydney.
