ENGLISH

Applied Mathematics with Open-Source Software: Operational Research Problems with Python and R

By Vincent Knight , Geraint Palmer

Book information

Publisher
Chapman and Hall/CRC
Year
2022
ISBN
0367348683, 9780367348687
Language
english
Format
PDF
Filesize
7 MB (7738881 bytes)
Series
Chapman & Hall/CRC Series in Operations Research
Edition
1
Pages
142\153
Time added
2022-04-10 16:00:12

Description

Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics. The book has an innovative structure with 4 sections of two chapters covering a large range of applied mathematical techniques: probabilistic modelling, dynamical systems, emergent behaviour and optimisation. The pairs of chapters in each section demonstrate different families of solution approaches. Each chapter starts with a problem, gives an overview of the relevant theory, shows a solution approach in R and in Python, and finally gives wider context by including a number of published references. This structure will allow for maximum accessibility, with minimal prerequisites in mathematics or programming as well as giving the right opportunities for a reader wanting to delve deeper into a particular topic. Features An excellent resource for scholars of applied mathematics and operational research, and indeed any academics who want to learn how to use open-source software. Offers more general and accessible treatment of the subject than other texts, both in terms of programming language but also in terms of the subjects considered. The R and Python sections purposefully mirror each other so that a reader can read only the section that interests them. An accompanying open-source repository with source files and further examples is posted online at https://bit.ly/3kpoKSd. Cover Half Title Series Page Title Page Copyright Page Contents Authors SECTION I: Getting Started CHAPTER 1: Introduction 1.1. WHO IS THIS BOOK FOR? 1.2. WHAT DO WE MEAN BY APPLIED MATHEMATICS? 1.3. WHAT IS OPEN-SOURCE SOFTWARE 1.4. HOW TO GET THE MOST OUT OF THIS BOOK 1.5. HOW CODE IS WRITTEN IN THIS BOOK SECTION II: Probabilistic Modelling CHAPTER 2: Markov Chains 2.1. PROBLEM 2.2. THEORY 2.3. SOLVING WITH PYTHON 2.4. SOLVING WITH R 2.5. WIDER CONTEXT CHAPTER 3: Discrete Event Simulation 3.1. PROBLEM 3.2. THEORY 3.2.1. Event Scheduling Approach 3.2.2. Process-Based Simulation 3.3. SOLVING WITH PYTHON 3.4. SOLVING WITH R 3.5. WIDER CONTEXT SECTION III: Dynamical Systems CHAPTER 4: Differential Equations 4.1. PROBLEM 4.2. THEORY 4.3. SOLVING WITH PYTHON 4.4. SOLVING WITH R 4.5. WIDER CONTEXT CHAPTER 5: Systems Dynamics 5.1. PROBLEM 5.2. THEORY 5.3. SOLVING WITH PYTHON 5.4. SOLVING WITH R 5.5. WIDER CONTEXT SECTION IV: Emergent Behaviour CHAPTER 6: Game Theory 6.1. PROBLEM 6.2. THEORY 6.3. SOLVING WITH PYTHON 6.4. SOLVING WITH R 6.5. WIDER CONTEXT CHAPTER 7: Agent-Based Simulation 7.1. PROBLEM 7.2. THEORY 7.3. SOLVING WITH PYTHON 7.4. SOLVING WITH R 7.5. WIDER CONTEXT SECTION V: Optimisation CHAPTER 8: Linear Programming 8.1. PROBLEM 8.2. THEORY 8.3. SOLVING WITH PYTHON 8.4. SOLVING WITH R 8.5. WIDER CONTEXT CHAPTER 9: Heuristics 9.1. PROBLEM 9.2. THEORY 9.3. SOLVING WITH PYTHON 9.4. SOLVING WITH R 9.5. WIDER CONTEXT Bibliography Index

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