Nature-Inspired Optimization Algorithms with Java : A Look at Optimization Techniques

Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java. You'll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You'll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You'll examine the use of each algorithm in specific industry scenarios such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications. Nature-Inspired Optimization Algorithms with Java is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them. What You'll Learn Study optimization and its problems Examine nature-inspired algorithms such as Particle Swarm, Gray wolf, etc. See how nature-inspired algorithms are being used to solve optimization problems Use Java for solving the different nature-inspired algorithms with real-world examples Who This Book Is For Software developers/architects who are looking to hone their skills in area of problem solving related to optimization with Java. Table of Contents About the Author About the Technical Reviewer Introduction Chapter 1: Introduction to Optimization: Problems and Techniques Optimization at a Glance Optimization Problems Optimization Techniques Metaheuristic Techniques for Optimization Reductionism and Emergence Self-Organization Exploration vs. Exploitation Workflow for Metaheuristic Techniques Benchmark Functions for Metaheuristic Techniques Summary Chapter 2: Mammals: Whale, Gray Wolf, and Bat Optimization History: Whales Encircling Prey Exploitation Phase: Bubble-Net Attacking Method Whale Flowchart Whale Pseudocode Whale Prerequisites and Code Executing the Whale Code History: Gray Wolves How Gray Wolf Optimization Works Searching (Exploration) Encircling (Exploration) Attacking (Exploitation) Gray Wolf Flowchart Gray Wolves Pseudocode Gray Wolves Prerequisites and Code Executing the Wolf Code History: Bats Bat Flowchart Bats Pseudocode Bats Prerequisites and Bat Code Executing the Bat Code Summary Chapter 3: Birds: Particle Swarm and Cuckoo Search Optimization History: Particle Swarm Birds of a Feather Flock Together Particle Swarm Optimization (PSO) Algorithm PSO Algorithm Flowchart PSO Pseudocode PSO Prerequisites and Code Executing the Completed PSO Code History: Cuckoo Search Brood Parasitism Lévy Flight Cuckoo Search Optimization (CSO) Algorithm CSO Flowchart CSO Pseudocode CSO Prerequisites and Code Executing the Code Output Summary Chapter 4: Insects: Firefly Optimization History Algorithm Flowchart Pseudocode Prerequisites and Code Executing the Code Output Summary Chapter 5: Sea Creatures: Salp Swarm Optimization History Salp Swarm Algorithm Flowchart Pseudocode Prerequisites and Code Executing the Code Output Summary Index Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java.You'll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You'll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You'll examine the use of each algorithm in specific industry scenarios such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications. __Nature-Inspired Optimization Algorithms with Java__ is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them. **What You'll Learn*** Study optimization and its problems * Examine nature-inspired algorithms such as Particle Swarm, Gray wolf, etc. * See how nature-inspired algorithms are being used to solve optimization problems * Use Java for solving the different nature-inspired algorithms with real-world examples **Who This Book Is For** Software developers/architects who are looking to hone their skills in area of problem solving related to optimization with Java. Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java. You'll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You'll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You'll examine the use of each algorithm in specific industry scenarios such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications. Nature-Inspired Optimization Algorithms with Java is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them. You will: Study optimization and its problems Examine nature-inspired algorithms such as Particle Swarm, Gray wolf, etc. See how nature-inspired algorithms are being used to solve optimization problems Use Java for solving the different nature-inspired algorithms with real-world examples