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Lec 9 Simulations and Algorithmic Implementation of Particle Swarm Optimization

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Lessons List | 27 Lesson
Evolutionary Computation for Single and Multi Objective Optimization Intro Video
00:06:28

Evolutionary Computation for Single and Multi Objective Optimization Intro Video
Lec 1 Introduction to Optimization
00:50:09

Lec 1 Introduction to Optimization
Lec 2 Introduction to Evolutionary Computation
01:10:28

Lec 2 Introduction to Evolutionary Computation
Lec 3 Binary Coded Genetic Algorithm BGA
01:11:11

Lec 3 Binary Coded Genetic Algorithm BGA
Lec 4 Operators and Simulations of Binary Coded Genetic Algorithm
01:09:00

Lec 4 Operators and Simulations of Binary Coded Genetic Algorithm
Lec 5 Real Coded Genetic Algorithm RGA
01:10:36

Lec 5 Real Coded Genetic Algorithm RGA
Lec 6 Operators and Simulations of Real Coded Genetic Algorithm
01:11:54

Lec 6 Operators and Simulations of Real Coded Genetic Algorithm
Lec 7 Algorithmic Implementation of BGA and RGA
00:52:57

Lec 7 Algorithmic Implementation of BGA and RGA
Lec 8 Particle Swarm Optimization PSO
01:00:51

Lec 8 Particle Swarm Optimization PSO
Lec 9 Simulations and Algorithmic Implementation of Particle Swarm Optimization
01:02:07

Lec 9 Simulations and Algorithmic Implementation of Particle Swarm Optimization
Lec 10 Differential Evolution DE
01:00:24

Lec 10 Differential Evolution DE
Lec 11 Simulations and Algorithmic Implementation of Differential Evolution
00:47:38

Lec 11 Simulations and Algorithmic Implementation of Differential Evolution
Lec 12 Constrained Optimization Introduction and Optimality
00:49:52

Lec 12 Constrained Optimization Introduction and Optimality
Lec 13 Penalty Function Methods for Evolutionary Computing Techniques
01:04:33

Lec 13 Penalty Function Methods for Evolutionary Computing Techniques
Lec 14 Evolutionary Computing Techniques Separation of Objective Function and Constraints
00:49:21

Lec 14 Evolutionary Computing Techniques Separation of Objective Function and Constraints
Lec 15 Simulations of Constraint Handling Techniques
00:56:02

Lec 15 Simulations of Constraint Handling Techniques
Lec 16 Simulations of Constraint Handling Techniques Part 2
00:32:12

Lec 16 Simulations of Constraint Handling Techniques Part 2
Lec 17 Introduction to Multi Objective Optimization Part 1
00:53:35

Lec 17 Introduction to Multi Objective Optimization Part 1
Lec 18 Introduction to Multi Objective Optimization Part 2
00:19:36

Lec 18 Introduction to Multi Objective Optimization Part 2
Lec 19 Multi Objective Optimization Ranking and Diversity
00:44:16

Lec 19 Multi Objective Optimization Ranking and Diversity
Lec 20 Classical Multi Objective Optimization Methods
01:04:02

Lec 20 Classical Multi Objective Optimization Methods
Lec 21 Non Dominated Genetic Algorithm NSGA II Introduction
01:04:27

Lec 21 Non Dominated Genetic Algorithm NSGA II Introduction
Lec 22 Non Dominated Genetic Algorithm NSGA II Simulations
01:04:22

Lec 22 Non Dominated Genetic Algorithm NSGA II Simulations
Lec 23 Strength Pareto Evolutionary Algorithm SPEA2 Introduction
00:50:18

Lec 23 Strength Pareto Evolutionary Algorithm SPEA2 Introduction
Lec 24 Strength Pareto Evolutionary Algorithm SPEA2 Simulations
00:50:47

Lec 24 Strength Pareto Evolutionary Algorithm SPEA2 Simulations
Lec 25 Performance Assessment of Multi Objective EC Techniques
00:27:25

Lec 25 Performance Assessment of Multi Objective EC Techniques
Lec 26 Closure of EC for Single and Multi Objective Optimization
00:20:06

Lec 26 Closure of EC for Single and Multi Objective Optimization

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Course Description

Algorithmic Implementation course in hindi, in this course covers practical aspects of turning algorithms into functional code, emphasizing efficient execution techniques.
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