## Course Detail

 Course Name Multidisciplinary Design Optimization Course Code 19AEE453 Program B. Tech. in Aerospace Engineering Year Taught 2019

### Syllabus

##### Unit 1

Single Variable Optimization: Introduction to Optimization, Optimality Criteria – Bracketing Methods: Exhaustive Search Method, Bounding Phase Method, Region Elimination Methods, Golden Section Search Method, Gradient Based Methods: Newton-Raphson Method, Bisection Method, Secant Method, Cubic Search Method.

##### Unit 2

Multivariable Optimization: Optimality Criteria – Gradient Based Methods: Steepest Descent Method, Conjugate Direction Method, Conjugate Gradient Method and Newton’s Method – Constrained Optimization: Karush-Kuhn-Tucker Optimality Criteria, Direct Methods, Indirect Methods, Penalty Function Methods.

##### Unit 3

Global Optimization: Simulated Annealing, Genetic Algorithm, Particle Swarm Optimization, Multi-Objective Optimization – Pareto Optimality – Global Function /Weighted Sum.

### Objectives and Outcomes

Course Objectives

• The objective of this course is to provide the students with the basic concepts of optimization, the modeling skills necessary to formulate and solve the optimization problems.

Course Outcomes

• CO1: Understand the terms optimization, design variables, objective functions, constraints and the types of optimization.
• CO2: Understand the single variable, multi-variable optimization with and without constraints.
• CO3: Apply the suitable optimization algorithm for the given problem.
• CO4: Analyse the accuracy of the optimization algorithms.
• CO5: Understanding and apply the non-conventional optimization methods for multi-objective functions. and to know about types of non-conventional optimization methods.

CO – PO Mapping

 PO/PSO/ CO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3 CO1 3 2 1 1 3 1 2 CO2 3 2 1 1 3 1 2 CO3 3 3 2 1 1 3 3 2 3 CO4 3 3 1 1 3 2 2 CO5 3 3 2 1 1 3 3 2 3

### Textbook / References

Textbook(s)

• Kalyanmoy Deb, “Optimization for Engineering Design Algorithms and Examples”, 2nd edition, Prentice Hall of India, New Delhi, 2012.

Reference(s)

• Kalyanmoy Deb, “Multi-Objective Optimization using Evolutionary Algorithms”, Wiley, 2010.
• J. Arora, “Introduction to Optimum Design,” 3rd Edition, Elsevier, 2012.

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.

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