This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.

This book chooses the topic which is due to the editors'' experience in modeling projects in healthcare systems. Also, the transfer of experiences is the reason why mathematical modeling and decision making in the field of health are not given much attention. To this end, the new aspect of this book is the lack of reference needed to carry out projects in the field of health for researchers whose main expertise is not modeling. Students of health, mathematics, management, and industrial engineering fields are in the direct readership with this book. Different projects in the field of healthcare systems can use the topics presented in different chapters mentioned in this book.

This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.

This book chooses the topic which is due to the editors'' experience in modeling projects in healthcare systems. Also, the transfer of experiences is the reason why mathematical modeling and decision making in the field of health are not given much attention. To this end, the new aspect of this book is the lack of reference needed to carry out projects in the field of health for researchers whose main expertise is not modeling. Students of health, mathematics, management, and industrial engineering fields are in the direct readership with this book. Different projects in the field of healthcare systems can use the topics presented in different chapters mentioned in this book.