Workshop on Engineering Optimization Theory and Practice by Prof. S. S. Rao
About the Instructor
Prof. Rao has extensive teaching and research experience at Miami, Purdue, San Diego State University, Indian Institute of Technology Kanpur, and NASA Langley Research Center. Prof. Rao has published more than 182 technical papers in internationally reputed journals and more than 134 papers in conference proceedings in the areas of engineering optimization, reliability-based design, fuzzy systems, active control of structures, and vibration engineering. He has also published a number of books in these areas. He served as Associate Editor of the ASME Journal of Mechanisms, Transmissions, and Automaton in Design and the journal of Microelectronics and Reliability. He has also edited several conference proceedings and served as the Conference Chairman and Papers Review Chairman for the ASME Design Automation Committee. Currently, he serves on the editorial boards of Engineering Optimization and Reliability Engineering and System Safety.
He received the ASME Design Automation award in 2013 for his pioneering contributions to multi-objective optimization, fuzzy, interval and evidence theories.
Computer Aided Engineering Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Madras.
22-24, December, 2013
About the Course
The ever-increasing demand on engineers to lower production costs to with-stand competition has prompted engineers to look for optimization methods, to design and produce products both economically and efficiently. Optimization is a powerful tool of the trade for engineer in virtually every discipline. It provides engineers with a rigorous, systematic method for rapidly zeroing in on the most innovative, cost-effective solutions to some of today's most challenging engineering design problems. This course provides in-depth coverage of linear, nonlinear, dynamic, integer and stochastic programming techniques. Also included are new or recently developed methods, such as evolutionary algorithms and fuzzy optimization techniques. Case studies and current literature on engineering optimization are covered.
Contents of the Course
Introduction to optimization; Basic concepts; Terminology; Formulation of practical problems as optimization problems.
Classical optimization techniques: Solution of unconstrained and constrained problems; Kuhn-Tucker conditions.
Constrained nonlinear programming methods: Direct and indirect methods; Penalty function methods; Sequential linear and quadratic programming techniques; Methods of feasible directions.
Modern methods of optimization: Genetic algorithms; Ant colony techniques; Particle swarm optimization; Fuzzy optimization; Neural network-based optimization; Simulated annealing.
Numerical solution: Lab sessions and hands-on experience for solving optimization problems using MATLAB.
The intention of the workshop is provide training in the basics as well as applications orientated techniques of engineering optimization in a comprehensive manner.
Exposure to the most practical and up-to-date optimization techniques in use throughout a wide range of industries
Hands on experience on the state-of-art optimization software tools
Solving practical design problems and exposure to different case studies
Useful in formulating and solving optimization problems for practicing engineers as well as researchers
Who should attend?
- Practicing engineers
- Scientists and Research engineers
- Teaching staff
- Software developers
- Solution integrators
The participants should have at least two years of practical or teaching experience.