Practical Swarm Intelligence in Python Using. Swarm Intelligence and Evolutionary Algorithms to Solve Problems in Engineering and Science

Swarm intelligence and evolutionary algorithms are powerful approaches to solving optimization problems, or anything that can be cast as an optimization problem. This includes everything from designing neural network architectures (AutoML) to arranging products in a grocery store to maximize profit. This book introduces the reader to these techniques with a Python toolkit and many experiments. 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