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Introduction to nature-inspired optimization /
"Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strength...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Academic Press,
2017.
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| Edición: | First edition. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Introduction to Nature-Inspired Optimization; Copyright; Contents; About the Authors; Preface; Acknowledgment; Notation; 1 An Introduction to Optimization; 1.1 Introduction; 1.2 Classes of Optimization Problems; 1.3 Using Calculus to Optimize a Function; 1.4 A Brute Force Method!; 1.5 Gradient Methods; 1.6 Nature Inspired Optimization Algorithms; 1.7 Randomness in Nature Inspired Algorithms; 1.8 Testing Nature Inspired Algorithms; 1.9 Summary; 1.10 Problems; 2 Evolutionary Algorithms; 2.1 Introduction; 2.2 Introduction to Genetic Algorithms; 2.3 Alternative Methods of Coding
- 2.4 Alternative Methods of Selection for Mating2.5 Alternative Forms of Mating; 2.6 Alternative Forms of Mutation; 2.7 Theoretical Background to GAs; 2.8 Continuous or Decimal Coding; 2.9 Selected Numerical Studies Using the Continuous GA; 2.10 Some Applications of the Genetic Algorithm; 2.11 Differential Evolution; 2.12 Other Variants of Differential Evolution; 2.13 Numerical Studies; 2.14 Some Applications of Differential Evolution; 2.15 Summary; 2.16 Problems; 3 Particle Swarm Optimization Algorithms; 3.1 Origins of Particle Swarm Optimization; 3.2 The PSO Algorithm
- 3.3 Developments of the PSO Algorithm3.4 Selected Numerical Studies Using PSO; 3.5 A Review of Some Relevant Developments; 3.6 Some Applications of Particle Swarm Optimization; 3.7 Summary; 3.8 Problems; 4 The Cuckoo Search Algorithm; 4.1 Introduction; 4.2 Description of the Cuckoo Search Algorithm; 4.3 Modi cations of the Cuckoo Search Algorithm; 4.4 Numerical Studies of the Cuckoo Search Algorithm; 4.5 Extensions and Developments of the Cuckoo Search Algorithm; 4.6 Some Applications of the Cuckoo Search Algorithm; 4.7 Summary; 4.8 Problems; 5 The Fire y Algorithm; 5.1 Introduction
- 5.2 Description of the Fire y Inspired Optimization Algorithm5.3 Modi cations to the Fire y Algorithm; 5.4 Selected Numerical Studies of the Fire y Algorithm; 5.5 Developments of the Fire y Algorithm; 5.6 Some Applications of the Fire y Algorithm; 5.7 Summary; 5.8 Reader Exercises; 6 Bacterial Foraging Inspired Algorithm; 6.1 Introduction; 6.2 Description of the Bacterial Foraging Optimization Algorithm; 6.3 Modi cations of the BFO Search Algorithm; 6.4 Selected Numerical Studies of the BFO Search Algorithm; 6.5 Theoretical Developments of the BFO Algorithm
- 6.6 Some Applications of the Bacterial Foraging Optimization6.7 Summary; 6.8 Problems; 7 Arti cial Bee and Ant Colony Optimization; 7.1 Introduction; 7.2 The Arti cial Bee Colony Algorithm (ABC); 7.3 Modi cations of the Arti cial Bee Colony (ABC) Algorithm; 7.4 Selected Numerical Studies of the Performance of the ABC Algorithm; 7.5 Some Applications of Arti cial Bee Colony Optimization; 7.6 Description of the Ant Colony Optimization Algorithms (ACO); 7.7 Modi cations of the Ant Colony Optimization (ACO) Algorithm; 7.8 Some Applications of Ant Colony Optimization; 7.9 Summary; 7.10 Problems