# Introduction to Computational Models with Python

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- eBook:Introduction to Computational Models with Python
- Author:Jose M. Garrido
- Edition:1 edition
- Categories:
- Data:August 28, 2015
- ISBN:0367575531
- ISBN-13:9780367575533
- Language:English
- Pages:496 pages
- Format:PDF

**Book Description**

The book’s five sections present:

- An overview of problem solving and simple Python programs, introducing the basic models and techniques for designing and implementing problem solutions, independent of software and hardware tools
- Programming principles with the Python programming language, covering basic programming concepts, data definitions, programming structures with flowcharts and pseudo-code, solving problems, and algorithms
- Python lists, arrays, basic data structures, object orientation, linked lists, recursion, and running programs under Linux
- Implementation of computational models with Python using Numpy, with examples and case studies
- The modeling of linear optimization problems, from problem formulation to implementation of computational models

**Content**

Chapter 1. Problem Solving and Computing

Chapter 2. Simple Python Programs

Section II - Basic Programming Principles with Python

Chapter 3. Modules and Functions

Chapter 4. Program Structures

Chapter 5. The Selection Program Structure

Chapter 6. The Repetition Program Structure

Section III - Data Structures, Object Orientation, and Recursion

Chapter 7. Python Lists, Strings, and Other Data Sequences

Chapter 8. Object Orientation

Chapter 9. Object-Oriented Programs

Chapter 10. Linked Lists

Chapter 11. Recursion

Section IV - Fundamental Computational Models with Python

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 Polynomial Growth

Chapter 16. Empirical Models with Interpolation and Curve Fitting

Chapter 17. Using Arrays with Numpy

Chapter 18. Models with Matrices and Linear Equations

Chapter 19. Introduction to Models of Dynamical Systems

Section V - Linear Optimization Models

Chapter 20. Linear Optimization Modeling

Chapter 21. Solving Linear Optimization Models

Chapter 22. Sensitivity Analysis and Duality

Chapter 23. Transportation Models

Chapter 24. Network Models

Chapter 25. Integer Linear Optimization Models

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