Introduction to Computational Modeling Using C and Open-Source Tools

Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing the data. All source files, shell scripts, and additional notes are located at science.kennesaw.edu/~jgarrido/comp_models

The book first presents an overview of problem solving and the introductory concepts, principles, and development of computational models before covering the programming principles of the C programming language. The author then applies programming principles and basic numerical techniques, such as polynomial evaluation, regression, and other numerical methods, to implement computational models. He also discusses more advanced concepts needed for modeling dynamical systems and explains how to generate numerical solutions. The book concludes with the modeling of linear optimization problems.

Emphasizing analytical skill development and problem solving, this book helps you understand how to reason about and conceptualize the problems, generate mathematical formulations, and computationally visualize and solve the problems. It provides you with the foundation to understand more advanced scientific computing, including parallel computing using MPI, grid computing, and other techniques in high-performance computing.

Table of Contents

Chapter 1: Problem Solving and Computing
Chapter 2: Programs
Chapter 3: Modular Decomposition: Functions
Chapter 4: More Concepts of Computational Models
Chapter 5: Algorithms and Programs
Chapter 6: Selection
Chapter 7: Repetition
Chapter 8: Arrays
Chapter 9: Pointers
Chapter 10: Linked Lists
Chapter 11: Text Data
Chapter 12: Computational Models with Arithmetic Growth
Chapter 13: Computational Models with Quadratic Growth
Chapter 14: Models with Geometric Growth
Chapter 15: Computational Models with Polynomials
Chapter 16: Models with Interpolation and Curve Fitting
Chapter 17: Using Vectors with the GSL
Chapter 18: Matrices and Sets of Linear Equations
Chapter 19: Introduction to Dynamical Systems
Chapter 20: Linear Optimization Modeling
Chapter 21: Solving Linear Optimization Problems
Chapter 22: Sensitivity Analysis and Duality
Chapter 23: Transportation Models
Chapter 24: Network Models
Chapter 25: Integer Linear Optimization Models
Appendix A: GNU C Compiler Tool
Appendix B: Introduction to Linux