2020-21-Even

Even Semester

ME6806 Introduction to Engineering Optimization

L-T-P-Cr: 3- 0- 0- 3

Pre-requisite: Basic Intermediate (10+2) level mathematics.

Objectives: To solve the various types of basic optimization problems in engineering.

Outcome: Ability to explore and experience the scopes of applications of optimization techniques in real engineering problems.


Module 1: Introduction to Engineering Optimization. Historical Development of Optimization Techniques. Various areas of applications.

Module 2: Optimal Problem Formulation: Design variables, Constraints, Objective Function, Variable bounds. Engineering Optimization Problems. Optimization Algorithms.

Module 3: Single-variable Optimization Algorithms: Optimality Criteria. Bracketing Methods. Region Elimination Methods. Point-Estimation Method. Gradient-based Methods.

Module 4: Multi-variable Optimization Algorithms: Optimality Criteria. Direct Search Methods. Gradient-based Methods.

Module 5: Constrained Optimization Algorithms: Kuhn-Tucker Conditions. Transformation Methods. Sensitivity Analysis.

Module 6: Integer Programming. Introduction to Non-traditional Optimization Algorithms. Binary and Real-coded Genetic Algorithm..


Lecture No. 1: Introduction to Engineering Optimization. Various areas of applications, Optimal Problem Formulation, Design variables, Constraints. [PDF] [YouTube Video].

Lecture No. 2: Design variables, Design Constraints, Objective Function, Variable bounds. [PDF] [YouTube Video].

Lecture No. 3: Classification of Optimization Problems. [PDF] [YouTube Video].

Lecture No. 4: Classification of Optimization Problems. [PDF] [YouTube Video].

Lecture No. 5: Optimization Problems: Examples. [PDF] [YouTube Video].