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Recommendations... 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.
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| |  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.
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 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.
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| |  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.
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 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.
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 Concepts of Mathematical Modeling
by Walter J. Meyer
This text features examinations of classic models and a variety of applications. Each section is preceded by an abstract and statement of prerequisites. Includes exercises. 1984 edition.
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Products in Optimization Theory | | |  | Boundary Value Problems and Fourier Expansions
by Charles R. MacCluer
Based on modern Sobolev methods, this text integrates numerical methods and symbolic manipulation into an elegant viewpoint that is consonant with implementation by digital computer. 2004 edition. Includes 64 figures. Exercises.
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| | Concepts of Mathematical Modeling
by Walter J. Meyer
This text features examinations of classic models and a variety of applications. Each section is preceded by an abstract and statement of prerequisites. Includes exercises. 1984 edition.
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|  | Introductory Discrete Mathematics
by V. K . Balakrishnan
This concise, undergraduate-level text focuses on combinatorics, graph theory with applications to some standard network optimization problems, and algorithms. More than 200 exercises, many with complete solutions. 1991 edition.
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|  | 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.
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|  | 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.
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| | 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.
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| | | 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.
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