NOC:Evolutionary Computation for Single and Multi Objective Optimization

Lecture 1 - Introduction to Optimization

Lecture 2 - Introduction to Evolutionary Computation

Lecture 3 - Binary-Coded Genetic Algorithm (BGA)

Lecture 4 - Operators and Simulations of Binary-Coded Genetic Algorithm

Lecture 5 - Real-Coded Genetic Algorithm (RGA)

Lecture 6 - Operators and Simulations of Real-Coded Genetic Algorithm

Lecture 7 - Algorithmic Implementation of BGA and RGA

Lecture 8 - Particle Swarm Optimization (PSO)

Lecture 9 - Simulations and Algorithmic Implementation of Particle Swarm Optimization

Lecture 10 - Differential Evolution (DE)

Lecture 11 - Simulations and Algorithmic Implementation of Differential Evolution

Lecture 12 - Constrained Optimization: Introduction and Optimality

Lecture 13 - Penalty Function Methods for Evolutionary Computing Techniques

Lecture 14 - Evolutionary Computing Techniques: Separation of Objective Function and Constraints

Lecture 15 - Simulations of Constraint Handling Techniques - Part 1

Lecture 16 - Simulations of Constraint Handling Techniques - Part 2

Lecture 17 - Introduction to Multi-Objective Optimization - Part 1

Lecture 18 - Introduction to Multi-Objective Optimization - Part 2

Lecture 19 - Multi-Objective Optimization: Ranking and Diversity

Lecture 20 - Classical Multi-Objective Optimization Methods

Lecture 21 - Non-Dominated Genetic Algorithm: NSGA-II: Introduction

Lecture 22 - Non-Dominated Genetic Algorithm: NSGA-II: Simulations

Lecture 23 - Strength Pareto Evolutionary Algorithm: SPEA2: Introduction

Lecture 24 - Strength Pareto Evolutionary Algorithm: SPEA2: Simulations

Lecture 25 - Performance Assessment of Multi-Objective EC Techniques

Lecture 26 - Closure of EC for Single and Multi-Objective Optimization