Название: Exploring Operations Research with RАвтор: Jim Duggan
Издательство: CRC Press
Год: 2024
Страниц: 396
Язык: английский
Формат: pdf (true)
Размер: 52.1 MB
Exploring Operations Research with R shows how the R programming language can be a valuable tool – and way of thinking – which can be successfully applied to the field of operations research (OR). This approach is centred on the idea of the future OR professional as someone who can combine knowledge of key OR techniques (e.g., simulation, linear programming, data science, and network science) with an understanding of R, including tools for data representation, manipulation, and analysis. The core aim of the book is to provide a self-contained introduction to R (both Base R and the tidyverse) and show how this knowledge can be applied to a range of OR challenges in the domains of public health, infectious disease, and energy generation, and thus provide a platform to develop actionable insights to support decision making.
The central idea behind this book is that R is a valuable computational tool that can be applied to the field of operations research. R provides excellent features such as data representation, data manipulation, and data analysis. These features can be integrated with operations research techniques (e.g., simulation, linear programming and Data Science) to support an information workflow which can provide insights to decision makers, and so, to paraphrase the words of Jay W. Forrester, help convert information into action.
R is an open source programming language, with comprehensive support for mathematics and statistics. With the development of R’s tidyverse — an integrated system of packages for data manipulation, exploration, and visualization — the use of R has seen significant growth, across many domains. The Comprehensive R Archive Network (CRAN) provides access to thousands of special purpose R packages (for example ggplot2 for visualization), and these can be integrated into an analyst’s workflow.
Features:
Can serve as a primary textbook for a comprehensive course in R, with applications in OR
Suitable for post-graduate students in OR and data science, with a focus on the computational perspective of OR
The text will also be of interest to professional OR practitioners as part of their continuing professional development
Linked to a Github repository including code, solutions, data sets, and other ancillary material
The book comprises three parts, where each part contains thematically related chapters:
1. Part I introduces R, and provides a step-by-step guide to the key features of R. The initial focus is on base R, and data structures, including: vectors, matrices, lists, data frames, and tibbles. The building blocks of R — functions — are presented, along with important ideas including environments, functionals, and the S3 object system.
2. Part II presents R’s tidyverse and Shiny, where the main focus is on five packages: ggplot2, dplyr, tidyr, purrr, and shiny, as together these provide a versatile platform for rapidly analyzing, interpreting, and visualizing data.
3. Part III focuses on four practical examples of using R to support operations research methods. These include exploratory data analysis, linear programming, agent-based simulation, and system dynamics.
What you will learn:
You will learn how to program and manipulate data in R, how to harness the power of R’s tidyverse, and observe how R can be used to support problem solving within the field of operations research.
Who should read this book:
The book is primarily aimed at post-graduate students in operations research. With its coverage of R, the tidyverse, and applications in agent-based simulation and system dynamics, the book also supports continuing professional development for operations research practitioners. As R is presented from scratch, there are no prerequisites, although prior experience of a programming language would provide useful contextual knowledge.
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