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/3kpo KSd. |Applied Mathematics with Open-Source Software Operational Research Problems with Python and R | Mathematics