| Course Name | Multidisciplinary Design Optimization |
| Course Code | 23AEE444 |
| Program | B. Tech. in Aerospace Engineering |
| Credits | 3 |
| Campus | Coimbatore |
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.
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.
Global Optimization: Simulated Annealing, Genetic Algorithm, Particle Swarm Optimization, Multi-Objective Optimization – Pareto Optimality – Global Function /Weighted Sum.
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 optimizations.
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: 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 | PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | PO7 | PO8 | PO9 | PO10 | PO11 | PO12 | PSO1 | PSO2 | PSO3 |
| CO | |||||||||||||||
| 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 |
Evaluation Pattern
| Assessment | Internal | End Semester |
| Midterm Exam | 30 | |
| *Continuous Assessment (CA) | 30 | |
| End Semester | 40 |
*CA – Can be Quizzes, Assignment, Projects, and Reports
Text Book(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.
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