|Discrete Optimization Algorithms: with Pascal Programs |
by Maciej M. Syslo, Narsingh Deo, Janusz S. Kowalik
Upper-level undergraduates and graduate students will benefit from this treatment of discrete optimization algorithms, which covers linear and integer programming and offers a collection of ready-to-use computer programs. 1983 edition.
|Data Structures and Algorithm Analysis in C++, Third Edition |
by Dr. Clifford A. Shaffer
Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses C++ as the programming language.
|Mathematics for Algorithm and Systems Analysis |
by Edward A. Bender, S. Gill Williamson
Discrete mathematics is fundamental to computer science, and this text covers its ideas and mathematical language. Features counting and listing, functions, decision trees and recursion, and basic concepts of graph theory.
|Mathematical Theory of Computation |
by Zohar Manna
Attempting to make into a science the art of verifying computer programs (debugging), the author addresses both practical and theoretical aspects. This self-contained treatment includes selected concepts of computability theory and mathematical logic.
|Applied Nonstandard Analysis |
by Prof. Martin Davis
This applications-oriented text assumes no knowledge of mathematical logic in its development of nonstandard analysis techniques and their applications to elementary real analysis and topological and Hilbert space. 1977 edition.
|Computability and Unsolvability |
by Prof. Martin Davis
Classic graduate-level introduction to theory of computability. Discusses general theory of computability, computable functions, operations on computable functions, Turing machines self-applied, unsolvable decision problems, applications of general theory, mathematical logic, Kleene hierarchy, more.
|Approximation of Elliptic Boundary-Value Problems |
by Jean-Pierre Aubin
A marriage of the finite-differences method with variational methods for solving boundary-value problems, this self-contained text for advanced undergraduates and graduate students is intended to imbed this combination of methods into the framework of functional analysis.
|Finite Elements and Approximation |
by O. C. Zienkiewicz, K. Morgan
This book offers students of engineering and physics a comprehensive view of the principles involved in the finite element, with numerous illustrative examples and exercises. 1983 edition.
|An Introduction to the Approximation of Functions |
by Theodore J. Rivlin
Graduate-level text offers a concise, wide-ranging introduction to methods of approximating continuous functions by functions depending only on a finite number of parameters. Particular emphasis on approximation by polynomials. 1969 edition.
|Analytical Methods of Optimization |
by D. F. Lawden
Suitable for advanced undergraduates and graduate students, this text surveys the classical theory of the calculus of variations. Topics include static systems, control systems, additional constraints, the Hamilton-Jacobi equation, and the accessory optimization problem. 1975 edition.
|Applied Probability Models with Optimization Applications |
by Sheldon M. Ross
Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.
|Combinatorial Optimization: Networks and Matroids |
by Eugene Lawler
Perceptive text examines shortest paths, network flows, bipartite and nonbipartite matching, matroids and the greedy algorithm, matroid intersections, and the matroid parity problems. Suitable for courses in combinatorial computing and concrete computational complexity.
|Combinatorial Optimization: Algorithms and Complexity |
by Christos H. Papadimitriou, Kenneth Steiglitz
This graduate-level text considers the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; local search heuristics for NP-complete problems, more. 1982 edition.
|Optimization Theory for Large Systems |
by Leon S. Lasdon
Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Initial chapter on linear and nonlinear programming provide the foundation for the rest of the book. Appendixes.
|Optimization Theory with Applications |
by Donald A. Pierre
Broad-spectrum approach to important topic. Explores the classic theory of minima and maxima, classical calculus of variations, simplex technique and linear programming, optimality and dynamic programming, more. 1969 edition.
|Variational Methods in Optimization |
by Donald R. Smith
Highly readable text elucidates applications of the chain rule of differentiation, integration by parts, parametric curves, line integrals, double integrals, and elementary differential equations. 1974 edition.