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Li, Changhe

Intelligent optimization principles, algorithms and applications Changhe Li, Shoufei Han, Sanyou Zeng ...[and another] - 1a. Ed - Singapore Springer ; Hubei Province : China University of Geosciences Press 2024 - xxiii, 361 Paginas ilustraciones a color

Intro -- Preface -- Acknowledgments -- Contents -- Acronyms -- Part I Introduction and Fundamentals -- 1 Introduction -- 1.1 Optimization and Machine Learning -- 1.2 Optimization Problems -- 1.2.1 Mathematical Formulation -- 1.2.2 Continuous Optimization Versus Discrete Optimization -- 1.3 Optimization Algorithms -- 1.3.1 Deterministic Algorithms and Probabilistic Algorithms -- 1.3.2 Intelligent Optimization Techniques -- References -- 2 Fundamentals -- 2.1 Fitness Landscapes -- 2.1.1 Solution Space -- 2.1.2 Objective Space -- 2.1.3 Neighbourhood -- 2.1.4 Global Optimum -- 2.1.5 Local Optimum
2.2 Properties of Fitness Landscape -- 2.2.1 Modality -- 2.2.2 Ruggedness -- 2.2.3 Deceptiveness -- 2.2.4 Neutrality -- 2.2.5 Separability -- 2.2.6 Scalability -- 2.2.7 Domino Convergence -- 2.2.8 Property Control, Analysis, and Visualization -- 2.3 Computational Complexity -- 2.3.1 Complexity Measures -- 2.3.1.1 Time Complexity -- 2.3.1.2 Space Complexity -- 2.3.1.3 Ways of Measures -- 2.3.1.4 Time Versus Space -- 2.3.2 P Versus NP Problem -- References -- 3 Canonical Optimization Algorithms -- 3.1 Numerical Optimization Algorithms -- 3.1.1 Line Search -- 3.1.2 Steepest Descent Method
3.1.3 Newton Method -- 3.1.4 Conjugate Gradient Method -- 3.2 State Space Search -- 3.2.1 State Space -- 3.2.1.1 The Shortest Path Problem -- 3.2.1.2 The Travelling Salesman Problem -- 3.2.2 Uninformed Search -- 3.2.2.1 Breadth-First Search -- 3.2.2.2 Depth-First Search -- 3.2.2.3 Depth-Limited Search -- 3.2.3 Informed Search -- 3.2.3.1 Greedy Search -- 3.2.3.2 A* Search -- 3.2.3.3 Monte-Carlo Tree Search -- 3.3 Single-Solution-Based Random Search -- 3.3.1 Hill Climbing -- 3.3.2 Simulated Annealing -- 3.3.3 Iterated Local Search -- 3.3.4 Variable Neighborhood Search -- References
Part II Evolutionary Computation Algorithms -- 4 Basics of Evolutionary Computation Algorithms -- 4.1 Introduction -- 4.1.1 Biological Evolution -- 4.1.2 Origin of Evolutionary Algorithms -- 4.1.3 Basic Evolutionary Processes -- 4.1.4 Developments -- 4.1.5 Related Resources -- 4.2 Solution Representation -- 4.2.1 Binary Representation -- 4.2.2 Integer Representation -- 4.2.3 Real-Valued Representation -- 4.2.4 Tree Representation -- 4.2.5 The Effect of Representation -- 4.3 Selection -- 4.3.1 Parents Selection -- 4.3.2 Survivor Selection -- 4.3.3 Selection Pressure -- 4.4 Reproduction
4.4.1 Mutation -- 4.4.2 Recombination -- References -- 5 Popular Evolutionary Computation Algorithms -- 5.1 Genetic Algorithm -- 5.1.1 Basic Principle and Framework -- 5.1.2 Applications of Genetic Algorithms -- 5.2 Evolutionary Programming -- 5.2.1 The Emergence of Evolutionary Programming -- 5.2.2 The Classical Evolutionary Programming -- 5.2.2.1 Representation -- 5.2.2.2 Mutation -- 5.2.2.3 Selection -- 5.2.3 Framework and Parameter Settings -- 5.2.4 Recent Advances in Evolutionary Programming -- 5.3 Genetic Programming -- 5.3.1 Introduction -- 5.3.2 Genotype-Phenotype Mapping

9789819732852 9789819732869


Computación evolutiva--Programación (matemáticas)
Teoría de optimización--Análisis de sistemas
Inteligencia artificial--Algoritmos computacionales

006.3



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