Mathematical Optimization: Fundamentals and Applications
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Mathematical optimization, often known as mathematical programming, is the process of choosing, from among a group of potential solutions, one that is optimal with relation to a set of predetermined criteria. Discrete optimization and continuous optimization are the two subfields that make up the majority of this field. Problems related to optimization appear in each and every one of the quantitative subfields, from computer science and engineering to operations research and economics. For millennia, the field of mathematics has been interested in the creation of methods that may solve these problems.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Mathematical optimization
Chapter 2: Brachistochrone curve
Chapter 3: Curve fitting
Chapter 4: Deterministic global optimization
Chapter 5: Goal programming
Chapter 6: Least squares
Chapter 7: Process optimization
Chapter 8: Simulation-based optimization
Chapter 9: Calculus of variations
Chapter 10: Vehicle routing problem
(II) Answering the public top questions about mathematical optimization.
(III) Real world examples for the usage of mathematical optimization in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of mathematical 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 mathematical optimization.
