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{ "item_title" : "Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems", "item_author" : [" Xi-Ren Cao "], "item_description" : "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 extension of the Hamilton-Jacobi-Bellman optimality condition from smooth to semi-smooth value functions by derivation of explicit optimality conditions at semi-smooth points and application of this result to degenerate and reflected processes;proof of semi-smoothness of the value function at degenerate points;attention to the under-selectivity issue for the long-run average and bias optimality; discussion of state classification for time nonhomogeneous continuous processes and multi-class optimization; anddevelopment of the multi-dimensional Tanaka formula for semi-smooth functions and application of this formula to stochastic control of multi-dimensional systems with degenerate points.The book will be of interest to researchers and students in the field of stochastic control andperformance optimization alike.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/03/041/848/3030418480_b.jpg", "price_data" : { "retail_price" : "169.99", "online_price" : "169.99", "our_price" : "169.99", "club_price" : "169.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems|Xi-Ren Cao

Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

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Overview

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 extension of the Hamilton-Jacobi-Bellman optimality condition from smooth to semi-smooth value functions by derivation of explicit optimality conditions at semi-smooth points and application of this result to degenerate and reflected processes;
  • proof of semi-smoothness of the value function at degenerate points;
  • attention to the under-selectivity issue for the long-run average and bias optimality;
  • discussion of state classification for time nonhomogeneous continuous processes and multi-class optimization; and
  • development of the multi-dimensional Tanaka formula for semi-smooth functions and application of this formula to stochastic control of multi-dimensional systems with degenerate points.

The book will be of interest to researchers and students in the field of stochastic control andperformance optimization alike.

This item is Non-Returnable

Details

  • ISBN-13: 9783030418489
  • ISBN-10: 3030418480
  • Publisher: Springer
  • Publish Date: May 2021
  • Dimensions: 9.21 x 6.14 x 0.8 inches
  • Shipping Weight: 1.19 pounds
  • Page Count: 365

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