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Course Detail

Course Name Optimization Techniques
Course Code 19MAT213
Program B. Tech. in Computer and Communication Engineering
Semester Four
Year Taught 2019


Introduction: Optimization – optimal problem formulation, engineering optimization problems, optimization algorithms, numerical search for optimal solution.

Single Variable optimization: Optimality criteria, bracketing methods – exhaustive search method, bounding phase method- region elimination methods – interval halving, Fibonacci search, golden section search, point estimation method- successive quadratic search, gradient based methods.

Multivariable Optimization: Optimality criteria, unconstrained optimization – solution by direct substitution, unidirectional search – direct search methods evolutionary search method, simplex search method, Hook-Jeeves pattern search method, gradient based methods – steepest descent, Cauchy’s steepest descent method, Newton’s method, conjugate gradient method – constrained optimization. Kuhn-Tucker conditions.


  • S.S. Rao, “Optimization Theory and Applications”, Second Edition, New Age International (P) Limited Publishers, 1995


  • Kalyanmoy Deb, “Optimization for Engineering Design Algorithms and Examples”, Prentice Hall of India, New Delhi, 2004.
  • Edwin K.P. Chong and Stanislaw H. Zak, “An Introduction to Optimization”, Second Edition, Wiley-Interscience Series in Discrete Mathematics and Optimization, 2004.
  • M. Asghar Bhatti, “Practical Optimization Methods: with Mathematics Applications”, Springer Verlag Publishers, 2000.

Evaluation Pattern

Assessment Internal External
Periodical 1 (P1) 15
Periodical 2 (P2) 15
*Continuous Assessment (CA) 20
End Semester 50
*CA – Can be Quizzes, Assignment, Projects, and Reports.

Objectives and Outcomes


  • To understand the concept of search space and optimality for solutions of engineering problems.
  • To understand some computation techniques for optimizing single variable functions.
  • To carry out various computational techniques for optimizing severable variable functions.

Course Outcomes

  • CO1: Understand different types of Optimization Techniques in engineering problems. Learn Optimization methods such as Bracketing methods, Region elimination methods, Point estimation methods.
  • CO2: Learn Optimizations Techniques in single variables problems.
  • CO3: Learn unconstrained Optimizations Techniques in single variables problems
  • CO4: Learn constrained optimization techniques and Kuhn-Tucker conditions

CO – PO Mapping

CO1 2 2 1 1
CO2 1 2 3 1
CO3 2 2 2 2
CO4 2 2 1 1 1

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