Unique treatment presents broad spectrum of approaches with balance between classical and modern techniques. Topics include classical theory of minima and maxima, classical calculus of variations, the simplex technique and linear programming, search techniques and nonlinear programming, optimality and dynamic programming, and more. Many detailed problems, examples. 1969 edition.
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.
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.
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.
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.
Concepts of Mathematical Modeling by Walter J. Meyer This text features a variety of applications, and examinations of classic models. Each section is preceded by an abstract and statement of prerequisites. Includes exercises. 1984 edition.
Nonlinear Programming: Analysis and Methods by Mordecai Avriel This text provides an excellent bridge between principal theories and concepts and their practical implementation. Topics include convex programming, duality, generalized convexity, analysis of selected nonlinear programs, techniques for numerical solutions, and unconstrained optimization methods.
Geometry and Convexity: A Study in Mathematical Methods by Paul J. Kelly, Max L. Weiss This text assumes no prerequisites, offering an easy-to-read treatment with simple notation and clear, complete proofs. From motivation to definition, its explanations feature concrete examples and theorems. 1979 edition.
