Slide 1
I Algorithms
Swarm Algorithms
What is Swarm Optimization?
A High-Level Taxonomy
A Brief Visit To The Zoo
Setting The Stage
Our General Approach
Objectives
Boundaries
Initializers
Are We Done Yet?
Inertia
Setting Up An Optimization
Random Optimization
Good Enough For Now
The RO Class
Optimize
Initialize
Step
Done
CandidatePositions
Evaluate
Results
Testing the RO Class
Particle Swarm Optimization
Making Sense of the World
Canonical PSO
Bare Bones PSO
Configuring a Particle Swarm
The PSO Class
Optimize
Initialize
Step
Done
NeighborhoodBest
RingNeighborhood
BareBonesUpdate
Evaluate
Results
Testing the PSO Class
New Kids On The Block
Jaya
Description
Implementation
The Grey Wolf Optimizer
Description
Implementation
Testing Jaya and GWO
Success or Failure?
Dispersion
Convergence
Precision
Runtime
Evaluation
Genetic Algorithm
Making Darwin Proud
The GA Class
Step
Evolve
Mutate
Crossover
Testing the GA Class
Modifying Population Size and Generations
Modifying CR, F, and
Comparison with Other Algorithms
Higher-Dimensional Searches
Differential Evolution
Unnatural Mutation
Configuring DE
The DE Class
Step
CandidatePositions
Candidate
Testing the DE Class
Experiments with a 2D Gaussian
Modifying CR and F
Comparing DE to Other Algorithms
II Experiments
Initial Experiments
Standard Test Functions
The 0-1 Knapsack
The Problem
The Setup
The Results
Curve Fitting
The Problem
The Setup
The Results
Training a Neural Network
The Problem
The Setup
The Results
Images
Image Registration
The Problem
The Setup
The Results
Image Segmentation
The Problem
The Setup
The Results
Image Enhancement
The Problem
The Setup
The Results
Music
Setting the Stage
Tools
Building Melodies
Learning and Merging Melodies
Learning Similar Melodies
Learning Melodies from Scratch
The Code
The Experiments
Cell Towers and Circles
Cell Towers
The Setup
The Code
The Experiments
Packing Circles
The Code
The Experiments
Summary
Grocery Store Simulation
The Design
Inventory
Stores
Shoppers
Running the Simulation
The Shopper
The Store
The Simulation
Testing the Algorithms
Working with RO
Varying the Number of Shoppers
Discussion