Each chapter concludes with a set of exercises, some of which take the form of case studies that, while fictitious, reflect realistic applications. The book is further supplemented by a Python package, pyloa . At the end of each chapter, examples show how classes and routines from this package can be applied to solve selected location problems introduced in the chapter.

This book is intended for graduate students in operations research, applied mathematics, mathematics?economics, industrial engineering, and business administration with a focus on analytics or quantitative methods. It is also a valuable resource for university instructors designing 5-15 ECTS courses on location?planning optimization, as well as for researchers and practitioners seeking a thorough introduction to optimisation models and methods for facility location planning.