Course Detail

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

Syllabus

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.

Textbook

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

Reference

• 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

Objectives

• 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

 PO/PSO/CO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 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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