EM502: Optimization

Basic Details:

Course Code: EM 502
Credits: 3
Pre-requisites: None
Compulsory/Optional: Optional

Aim :

To introduce nonlinear programming methods and their application to solve engineering and real life problems

Intended Learning Outcomes:

On successful completion of the course, the students should be able to;

Apply and analyze optimization methods for functions of single variable.
Apply and analyze optimization methods for functions of many variables with or without constraints.
Formulate engineering problems as optimization problems and solve them adopting appropriate optimization algorithms.

Couse Content:

Overview of Optimization

Theory of Optimization

Single variable, multivariable unconstrained and constrained, Lagrange multipliers, KKT conditions.

Numerical Optimization

Single variable Optimization: Elimination methods, bracketing methods, interpolation methods, root finding methods.

Multivariable Optimization (Unconstrained): Direct search methods, indirect search (descent) methods.

Constrained Optimization: Direct search methods, indirect methods, penalty methods, transformation methods, linearized methods.

Non-conventional Optimization Algorithms

Introduction to genetic algorithms, simulated annealing, swarm algorithm, and ant algorithm

Applications of Optimization

Mathematical modelling and design of, engineering and real life systems, nonlinear curve fitting.

Time Allocation (Hours):

Lectures

Assignments

Tutorials

Practical

Recommended Texts:

Singiresu S. Rao, Engineering Optimization, 4th edition, (2009), John Wiley & Sons Inc., NJ.
Kalyanamoy Debb, Optimization for Engineering Design (2005), Prentice Hall of India.

Assessment:

In - course: