Linear Complementarity, Linear and Nonlinear Programming
by Katta G. Murty
Number of pages: 613
This book provides an in-depth and clear treatment of all the important practical, technical, computational, geometric, and mathematical aspects of the Linear Complementarity Problem, Quadratic Programming, and their various applications. It discusses clearly the various algorithms for solving the LCP, presents their efficient implementation for the computer, and discusses their computational complexity. It presents the practical applications of these algorithms and extensions of these algorithms to solve general nonlinear programming problems.
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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 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.
by D. P. Williamson, D. B. Shmoys - Cambridge University Press
This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. It is organized around techniques for designing approximation algorithms, including greedy and local search algorithms.
by P.-A. Absil, R. Mahony, R. Sepulchre - Princeton University Press
Many science and engineering problems can be rephrased as optimization problems on matrix search spaces endowed with a manifold structure. This book shows how to exploit the structure of such problems to develop efficient numerical algorithms.