An Introduction to Mathematical Modeling by Edward A. Bender Accessible text features over 100 reality-based examples pulled from the science, engineering and operations research fields. Prerequisites: ordinary differential equations, continuous probability. Numerous references. Includes 27 black-and-white figures. 1978 edition.
Vectors, Tensors and the Basic Equations of Fluid Mechanics by Rutherford Aris Introductory text for engineers, physicists, and applied mathematicians applies the mathematics of Cartesian and general tensors to physical field theories. Advanced undergraduate-graduate level. Exercises. Appendixes.
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.
Theory of Scheduling by Richard W. Conway, William L. Maxwell, Louis W. Miller This comprehensive text explores the mathematical models underlying the theory of scheduling. Organized according to scheduling problem type, it examines 3 solution techniques: algebraic, probabilistic, and Monte Carlo simulation by computer. 1967 edition.
Building Models by Games by Wilfrid Hodges This volume covers basic model theory and examines such algebraic applications as completeness for Magidor-Malitz quantifiers, Shelah's recent and sophisticated omitting types theorem for L(Q), and applications to Boolean algebras. Over 160 exercises. 1985 edition.
An Introduction to Identification by J. P. Norton Suitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition.
