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Solving Optimization Problems with the Heuristic Kalman Algorithm: New Stochastic Methods
Hardcover
Series: Springer Optimization and Its Applications, Book 212
General MathematicsProgramming
ISBN13: 9783031524585
Publisher: Springer
Published: Mar 22 2024
Pages: 286
Weight: 1.34
Height: 0.75 Width: 6.14 Depth: 9.21
Language: English
The main optimization tool used in this book to tackle the problem of nonconvexity is the Heuristic Kalman Algorithm (HKA). The main characteristic of HKA is the use of a stochastic search mechanism to solve a given optimization problem. From a computational point of view, the use of a stochastic search procedure appears essential for dealing with non-convex problems.
The Heuristic Kalman Algorithm discussed in this book applies to many fields such as robust structured control, electrical engineering, mechanical engineering, machine learning, reliability, and preference models. This large coverage of practical optimization problems makes this text very useful to those working on and researching systems design. The intended audience includes industrial engineers, postgraduates, and final-year undergraduates in various fields of systems design.
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