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Course Detail

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


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



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


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


  • 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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