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This monograph applies the relative optimization approach to time nonhomogeneous continuous-time and continuous-state dynamic systems. The approach is intuitively clear and does not require deep knowledge of the mathematics of partial differential equations. The topics covered have the following distinguishing features: long-run average with no under-selectivity, non-smooth value functions with no viscosity solutions, diffusion processes with degenerate points, multi-class optimization with state classification, and optimization with no dynamic programming.
The book begins with an introduction to relative optimization, including a comparison with the traditional approach of dynamic programming. The text then studies the Markov process, focusing on infinite-horizon optimization problems, and moves on to discuss optimal control of diffusion processes with semi-smooth value functions and degenerate points, and optimization of multi-dimensional diffusion processes. The book concludes with a brief overview of performance derivative-based optimization.
Among the more important novel considerations presented are:
The book will be of interest to researchers and students in the field of stochastic control andperformance optimization alike.
Published by: Springer
Publication Date: 2020-05-14
Format: Hardcover
ISBN-13: 9783030418458
DOI: 10.1007/978-3-030-41846-5
Dimensions: 235cm x155cm
Pages: 365