CURRENTLY SOLD OUT

Introduction to Global Optimization Exploiting Space-Filling Curves by Yaroslav D. Sergeyev, Daniela Lera, Roman G. Strongin (Paperback, 2013)

Introduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization. The authors look at a family of derivative-free numerical algorithms applying space-filling curves to reduce the dimensionality of the global optimization problem; along with a number of unconventional ideas, such as adaptive strategies for estimating Lipschitz constant, balancing global and local information to accelerate the search. Convergence conditions of the described algorithms are studied in depth and theoretical considerations are illustrated through numerical examples. This work also contains a code for implementing space-filling curves that can be used for constructing new global optimization algorithms. Basic ideas from this text can be applied to a number of problems including problems with multiextremal and partially defined constraints and non-redundant parallel computations can be organized. Professors, students, researchers, engineers, and other professionals in the fields of pure mathematics, nonlinear sciences studying fractals, operations research, management science, industrial and applied mathematics, computer science, engineering, economics, and the environmental sciences will find this title useful .

Subject Area
Data Analysis
Author
Yaroslav D. Sergeyev, Daniela Lera, Roman G. Strongin
Publication Name
Introduction to Global Optimization Exploiting Space-Filling Curves
Format
Paperback
Language
English
Subject
Computer Science, Mathematics, Management
Publication Year
2013
Type
Textbook
Number of Pages
125 Pages

Best Selling in Adult Learning & University

Current slide {CURRENT_SLIDE} of {TOTAL_SLIDES}- Best Selling in Adult Learning & University

Current slide {CURRENT_SLIDE} of {TOTAL_SLIDES}- Save on Adult Learning & University