Springer Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling: 236 (International Series in Operations Research & Management Science, 236)

The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS. From the Back Cover The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS. About the Author Ghaith Rabadi is a faculty member in the Department of Engineering Management & Systems Engineering at Old Dominion University.  He received his Ph.D. and M.S. in Industrial Engineering from the University of Central Florida (UCF) in 1999 and 1996 respectively, and his B.S. in Industrial Engineering from the University of Jordan in 1992. Prior to joining the faculty at Old Dominion in 2002, he was a post doc for one year and a Visiting Assistant professor at the Industrial Engineering & Management Systems Department at UCF for another year.  He has published numerous journal and conference papers and contributed several book chapters in edited volumes. His research has been funded by NASA, Department of Homeland Security, Virginia Port Authority, Northrop Grumman Shipbuilding, MITRE Corporation, STIHL, CACI, Sentara Hospitals and Qatar National Research Fund of Qatar Foundation. He received the NASA Faculty Fellowship where he worked at NASA Langley Research Center in Virginia as a faculty fellow. He also received the Fulbright Specialist Program award. His research and teaching interests include Planning and Scheduling, Operations Research, Simulation Modeling and Analysis, Analytics, and Supply Chain Management and Logistics. He founded the International Journal of Planning and Scheduling in 2010 and has been serving as its Chief Editor since then.