Table of Contents

Problem Solving: Problem Solving and Computing. Simple Python Programs. Basic Programming Principles with Python: Modules and Functions. Program Structures. The Selection Program Structure. The Repetition Program Structure. Data Structures, Object Orientation, and Recursion: Python Lists, Strings, and Other Data Sequences. Object Orientation. Object-Oriented Programs. Linked Lists. Recursion. Fundamental Computational Models with Python: Computational Models with Arithmetic Growth. Computational Models with Quadratic Growth. Models with Geometric Growth. Computational Models with Polynomial Growth. Empirical Models with Interpolation and Curve Fitting. Using Arrays with Numpy. Models with Matrices and Linear Equations. Introduction to Models of Dynamical Systems. Linear Optimization Models: Linear Optimization Modeling. Solving Linear Optimization Models. Sensitivity Analysis and Duality. Transportation Models. Network Models. Integer Linear Optimization Models.

About the Author

José M. Garrido is a professor in the Department of Computer Science at Kennesaw State University. Dr. Garrido is the author of several books and numerous research papers. His research interests include software development, operating systems, computational modeling, object-oriented simulation, and system formal specification.