Scheduling

This book provides expanded Discussion and Comments and References sections at the end of each chapter, creating a spotlight on practical applications of the theory presented in that chapter. New topics include rules for stochastic parallel machine scheduling and for stochastic online scheduling, models of flow shops with reentry, fixed parameter tractability, machine learning applications in scheduling, and new designs and implementations of scheduling systems. The main structure of the book as per previous edition consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part, it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped and streamlined and the references have been made up-to-date. Theoreticians and practitioners alike find this book of interest. Graduate students in operations management, operations research, industrial engineering, and computer science find the book an accessible and invaluable resource. Scheduling: Theory, Algorithms, and Systems serves as an essential reference for professionals working on scheduling problems in manufacturing, services, and other environments.