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Computational Optimization, Methods and Algorithms

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Cover of 'Computational Optimization, Methods and Algorithms'

Table of Contents

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    Book Overview
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    Chapter 1 Computational Optimization: An Overview
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    Chapter 2 Optimization Algorithms
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    Chapter 3 Surrogate-Based Methods
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    Chapter 4 Derivative-Free Optimization
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    Chapter 5 Maximum Simulated Likelihood Estimation: Techniques and Applications in Economics
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    Chapter 6 Optimizing Complex Multi-location Inventory Models Using Particle Swarm Optimization
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    Chapter 7 Traditional and Hybrid Derivative-Free Optimization Approaches for Black Box Functions
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    Chapter 8 Simulation-Driven Design in Microwave Engineering: Methods
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    Chapter 9 Variable-Fidelity Aerodynamic Shape Optimization
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    Chapter 10 Evolutionary Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization
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    Chapter 11 An Enhanced Support Vector Machines Model for Classification and Rule Generation
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    Chapter 12 Benchmark Problems in Structural Optimization
Attention for Chapter 5: Maximum Simulated Likelihood Estimation: Techniques and Applications in Economics
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