Random Optimization - Fundamentals and Applications

Fouad Sabry

Summary

What Is Random Optimization
 
Because it does not require the gradient of the problem to be optimized, random optimization (also known as RO) is a family of numerical optimization methods that can be used to functions that are neither continuous nor differentiable. These kinds of optimization approaches are also referred to as direct-search methods, derivative-free methods, and black-box methods.
 
How You Will Benefit
 
(I) Insights, and validations about the following topics:
 
Chapter 1: Random optimization
 
Chapter 2: Mathematical optimization
 
Chapter 3: Gradient
 
Chapter 4: Continuous function
 
Chapter 5: Differentiable function
 
Chapter 6: Normal distribution
 
Chapter 7: Evolution strategy
 
Chapter 8: Unimodality
 
Chapter 9: Limit (mathematics)
 
Chapter 10: Probability distribution
 
(II) Answering the public top questions about random optimization.
 
(III) Real world examples for the usage of random optimization in many fields.
 
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of random optimization' technologies.
 
Who This Book Is For
 
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of random optimization.

Available since: 07/01/2023.

Print length: 151 pages.

Science & Technology

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