iSIGHT 9'0: Theory, Concepts and Application

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iSIGHT 9.0 Theory, Concepts and Application

• Digging a little deeper into theory of iSIGHTs
  major optimization techniques and how to
  control/diagnose their use

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Who is Dave Powell?

• Co founder of Engineous Software
• Currently chair of Computing Sciences at Elon
  University
• Jack of all trades master of none
• Civil engineer degree - MS
• Business degree - MBA
• Computer Science degree PhD
• Thesis on Optimization (Interdigitation)
• Emphasis is application or hands on ( not a
  theory guy )
• Email is dpowell2_at_elon.edu
• Web site is www.elon.edu/dpowell2
• Click on Optimization 2005
• Phone is 336-278-6233

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Who is Therese Polito?

• PhD from Louisiana State University
• Joined Engineous from Ansys in 1998.
• Spent 7 years working with customers solving
  their design problems with iSIGHT and Fiper.
• Take advantage of her experience breadth,
  modeling experience and her knowledge of tricks
  of the trade.

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Class Prerequisites

• Familiarity with iSIGHT
• If you have not used for a while then
• Pair up with someone during labs
• Leverage Therese Polito
• Leverage Detroit representatives

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Topics

• Class Organization
• Nature and Diversity of Nonlinear Programs
• Lab

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Class Organization Major Topics

• Deterministic Optimization Models
• Improving Search
• Unconstrained Nonlinear Programming
• Constrained Nonlinear Programming

• Multiobjective Optimization

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Core Algorithms Packages
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References

• Hard copy handouts or pointers to Selective
  Optimization Packages from Developers
• Varied Developer Background
• Varied Developer Locations
• Varied Terminology
• Varied User Friendliness
• To diagnose a problem, you must speak the
  developers language and the iSIGHT Language.

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Course References

• Optimization in Operations Research Rardin -
  1998
• Numerical Optimization Techniques for Engineering
  Design with Applications Vanderplaats - 1999
• Optimization Concepts and Applications in
  Engineering Belegundu - 1999
• Introduction to Engineering Design Optimization
  Onwubiko - 2000
• Engineering Optimization Theory and Practice
  Rao 1996
• Multi-Objective Optimization using Evolutionary
  Algorithms Deb 2001
• Practical Management Science Winston 2001
• Engineering Optimization Methods and Applications
  Reklaitis 1983
• Applied Optimization with Matlab Programming,
  Venkataraman, 2002.

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Key Goals

• Understanding the client side iSIGHT Optimization
  Model Abstraction
• Understanding the internal representation of the
  iSIGHT Optimization Model
• Understanding the transformation between iSIGHT
  Model and Third Party Optimization Packages
• Give you conceptual background to understand
  options of each technique

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Middleman
iSIGHT
ADS
DownhillSimplex
MOST
NSGA2
NLPQL
GRG
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Walk Away Info

• Problem Formulation is critical
• Scaling
• Good initial starting point
• Use multiple starting points
• Read the optimizers diagnostic output

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Individual Objectives

• Name
• Company
• iSIGHT Experience
• What you hope to take from course?