Applied Mathematical Programming Using Algebraic Systems
by Bruce A. McCarl, Thomas H. Spreen
Publisher: Texas A&M University 2011
Number of pages: 567
This book is intended to both serve as a reference guide and a text for a course on Applied Mathematical Programming. The material presented will concentrate upon conceptual issues, problem formulation, computerized problem solution, and results interpretation. Solution algorithms will be treated only to the extent necessary to interpret solutions and overview events that may occur during the solution process.
Home page url
Download or read it online for free here:
by Thomas S. Ferguson - UCLA
From the table of contents: Stopping Rule Problems; Finite Horizon Problems; The Existence of Optimal Rules; Applications. Markov Models; Monotone Stopping Rule Problems; Maximizing the Rate of Return; Bandit Problems; Solutions to the Exercises.
by K.J.H. Law, A.M. Stuart, K.C. Zygalakis - arXiv.org
This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation. Authors develop a framework in which a Bayesian formulation of the problem provides the bedrock for the derivation and analysis of algorithms.
by Marius Durea, Radu Strugariu - De Gruyter Open
Starting with the case of differentiable data and the classical results on constrained optimization problems, continuing with the topic of nonsmooth objects involved in optimization, the book concentrates on both theoretical and practical aspects.
by Ian Craw - University of Aberdeen
The book describes the simplex algorithm and shows how it can be used to solve real problems. It shows how previous results in linear algebra give a framework for understanding the simplex algorithm and describes other optimization algorithms.