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Course Detail

Course Name Optimization Techniques in Engineering
Course Code 19MEE333
Program B. Tech. in Mechanical Engineering
Year Taught 2019

Syllabus

Unit 1

Introduction – Engineering applications – Statement of an optimization problem – Classifications of Optimization problems – Optimal problem formulation: Problems involving design and manufacturing – Optimality criteria – Classical optimization techniques – Kuhn-Tucker (KT) optimality conditions.

Unit 2

Non-linear programming: One dimensional minimization methods – Unconstrained optimization techniques – Constrained optimization techniques – Transformation methods – Interior and exterior penalty function method – Convergence and divergence of optimization algorithms – Complexity of algorithms.

Unit 3

Modern Methods in Optimization: Genetic Algorithm – Simulated Annealing – Particle Swarm Optimization – Neural Network based optimization – Optimization of Fuzzy systems – Multi-Objective optimization – Data Analytics and optimization using Machine learning approach.

Unit 4

Implementing optimization algorithmsinMatlab / R / Python environment and solving linear, non-linear, multi- objective un constrained and constrained optimization problems.

Objectives and Outcomes

Course Objectives

  • Impart knowledge on theory of optimization and conditions for optimality for unconstraint and constraint optimization problems
  • Inculcate modeling skills necessary to describe and formulate optimization problems in design and manufacturing
  • Familiarize with the working principle of optimization algorithms used to solve linear and non-linear problems
  • Train the students to solve optimization problems using software tools

Course Outcomes

  • CO1: Formulate the engineering problems as an optimization problem.
  • CO2: Apply necessary and sufficient conditions for a given optimization problem for optimality
  • CO3: Select appropriate solution methods and strategies for solving an optimization problem and interpret and analyze the solution obtained by optimization algorithms
  • CO4: Justify and apply the use of modern heuristic algorithms for solving optimization problems
  • CO5: Solve Engineering Design and Manufacturing related optimization problem using software tools.

CO – PO Mapping

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

Textbook

Textbook(s)

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.
  • S.S. Rao, Engineering optimization: Theory and Practice, New age international, 3rd edition, 2013.
  • K. Deb., Optimization for Engineering Design: Algorithms and Examples, PHI, 2nd Edition, 2012.
  • J. S. Arora, Introduction to Optimum Design, Academic press, 4th Edition, 2017.

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