Nature Inspired Optimization Algorithms
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Nature Inspired Optimization Algorithms Syllabus — Unit-wise Content
The official GTU curriculum for Nature Inspired Optimization Algorithms (subject code 3164303) as prescribed for AI & ML · Semester 6 divides the course into 6 units, covering 39 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3164303)Unit 1 Introduction to Algorithms and Optimization
- Introduction to algorithm
- fundamental of Optimization
- Types of optimization problems
- example of optimization
- formulation of optimization problem and classification of optimization algorithm
- applications of nature inspired optimization algorithm
- Travelling salesman and Knapsack Problem
Unit 2 Nature Inspired Algorithms
- Structure of NIOAS
- Traditional Vs
- Nature inspired algorithm
- Bio inspired algorithm
- Swarm Intelligence
- Diversification and Intensification
- Basics of Genetic Algorithm
- example of GA
Unit 3 Classical Optimization Algorithm
- Mathematical model for optimization
- linear Programming : Simplex and Revised Simplex
- Non-Linear Programming
- Dynamic Programming
- Integer Programming
- Stochastic programming Open Elective Subject Code : 3164303 Subject Name : Nature Inspired Optimization Algorithms
Unit 4 Nature Inspired Optimization Algorithms - 1
- Particle Swarm Optimization: swarm behavior and algorithm
- Differential Evolution: Algorithm
- Ant Colony Optimization: Ant colony characteristics
- travelling salesman problem and algorithm
- Fish School Search optimization algorithm
Unit 5 Nature Inspired Optimization Algorithm – 2
- Cuckoo Search optimization algorithm
- Binary Cuckoo Search algorithm
- Discrete Cuckoo algorithm
- Firefly algorithm
- Bat algorithm
- Crow search algorithm
- Flower Pollination algorithm
Unit 6 Combinatorial Optimization
- Travelling Salesman Problem (TSP)
- Graph Coloring Problem
- Job Scheduling problem
- Network Routing Problem
- Total Hours : 42 Textbook : 1
- Nature-Inspired Optimization Algorithms By Vasuki A
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