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A certificate of completed Continuing Education
Units (CEUs) will be granted at the end of this course.
8:00am - Registration and coffee (1st day only)
8:30am - Session begins
4:30pm - Adjournment
Breakfast, two refreshment breaks and lunch are provided daily.
Optimization is a proven technology that has been successfully applied in many fields, saving significantly for businesses and/or achieving optimal products and processes for engineering teams. This course covers concept of optimization, problem formulation, common optimization types, and solution strategies. The content covers classic gradient-based optimization methods and evolutionary algorithms, with an introduction to metamodel-based design optimization for problems with lengthy or expensive simulations. The workshop will be augmented with examples from engineering and businesses. Students will also apply Excel solver to solve practical optimization problems, see demonstrations of Matlab Optimization Toolbox, and OPTIP, a tool developed by Dr. Wang and his team.
This course is to enhance engineers and business (or NGO’s) managers with the thinking of quantitative optimization, and equip them with methods and tools to apply optimization in their daily activities.
- Junior/senior design engineers in all disciplines
- Junior/senior production or process engineers
- Managers for Design/Production/Supply Chain/Operations
- Project leaders
- Executives (e.g. VP operations) for businesses or NGO’s
- Healthcare efficiency team members
Program Outline (1.8 CEUs / 18 PDHs)
- Introduction of optimization with example applications
- “Optimal” thinking and problem formulation
- Types of optimization
- Analytical method
- Graphical method with practices
- Optimization methods without constraints
- Introduction to constrained optimization
- Steepest descent, Newton, and Quasi-Newton Methods
- How do you know you got the optimum? –The convergence conditions
- Introduction of Excel Solver
- Practices and problem solving with Excel Solver
- Matlab optimization toolbox demo with examples
- Evolutionary optimization and Genetic Algorithm (GA)
- Application examples and demo with Matlab GA toolbox
- Introduction of Metamodel-based Design Optimization
- Demo of OPTIP –Optimization Toolbox for Computationally-Intensive Problems
After Attending This Course You Will Be Able To:
- Understand the concepts of optimization
- Think “optimally”
- Formulate an optimization problem
- Perform basic mathematical transformation for optimization
- Identify the type of optimization problem and choose a suitable tool
- Apply Excel Solver to solve simple optimization problems
- Know how to select advanced optimization methods and tools for more practical problems
- Solve problems with no explicit equations
- Solve problems with computationally-intensive simulations such as finite element analysis, computational fluid dynamics, process simulation in Arena, and so on.
- Optimize based on physical experiments (no model at all)
This course will involve many examples from engineering design and businesses. Students will also have hands-on time by using a basic optimizer, Excel Solver, to solve practical problems. Students will also see demonstration of Matlab Optimization and GA toolboxes, as well as in-house tool OPTIP. It will be interactive.
A laptop with Microsoft Office Excel with the add-in Solver installed. Excel Solver is a free add-in coming with MS Excel. The installation varies a bit depends on your version.
Dr. Gary Wang, Ph.D., P.Eng.
Professor, Simon Fraser University
President, Optimum Engineering Consulting
Prof. Wang has been working in the area of optimization since 1992. He has worked with many companies including General Motors (GM), Rapid Electric Vehicles (REV), Ballard Power Systems, Manitoba Hydro, Phillips and Temro Industries, E. H. Price Ltd., Vansco Electronics Ltd., Monarch Industries, etc., as well as government organizations such as Winnipeg Health Region Authority and St. Paul’s Hospital in Vancouver. He and his students have published close to 50 journal articles and about 70 conference articles and technical reports in optimization and related topics. He and his team have developed a suite of state-of-the-art optimization methods for design optimization, which have been successfully applied to practical problems. He has being teaching optimization at universities since 1999.
Achievements and Recognitions:
- Geographically representing North America, serving as one of the four associate editors for the reputed International Journal of Engineering Optimization
- Recipient of 2007 Rh Award from University of Manitoba for outstanding research contribution in the Applied Science category.
- Recipient of the 2005 National I. W. Smith award for creative engineering from Canadian Society of Mechanical Engineering (CSME)
- Conference Chair for 2012 Design Automation Conference, a sub-conference in the world premium International Design Engineering Technology Conference (IDETC).
- Technical Program Chair for 2011 Design Automation Conference, a sub-conference in the world premium International Design Engineering Technology Conference (IDETC).
- One of the world leading researchers in the field of design optimization
Prof. Wang is a member of the following Associations: APEGBC, ASME, AIAA.
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