Pricing, inventory control, and scheduling are three departments that form a revenue management triangle. Scheduling is another means of matching consumer demand with supply. A carrier’s departure schedule defines its core product and is a key determinant of its profitability. The first section in this module looks at the scheduling process as a whole. It considers its importance, the complexity involved and provides an overview of what occurs in the long-, medium- and short-term at different levels in the organisation. In the second section, we focus on the medium-term planning phase and consider the goals and challenges of schedule design and fleet assignment. This third section looks at the short-term management of the current schedule. This includes any ad hoc departure cancellations or other capacity adjustments that are needed closer to departure.

Master scheduling is an essential planning tool that helps manufacturers synchronize their production cycle with actual market demand. The third edition of this easy-to-follow handbook helps you understand the basic and more advanced concepts of master scheduling, from implementation to capacity planning to final assembly techniques. Packed with handy checklists and examples, Master Scheduling, Third Edition delivers guidelines and techniques for a world-class master schedule.

Reflects exact and heuristic methods of scheduling techniques suitable for creating customized sequencing and scheduling systems for flexible manufacturing, project management, group and cellular manufacturing operations. Summarizes complex computational studies demonstrating how they work in practice. Contains new theories and techniques developed by the author. Includes a software disk to reinforce and practice the methods described.

Emphasizes a hands-on approach to learning statistical analysis and model building through the use of comprehensive examples, problems sets, and software applications With a unique blend of theory and applications, Simulation Modeling and Arena®, Second Edition integrates coverage of statistical analysis and model building to emphasize the importance of both topics in simulation. Featuring introductory coverage on how simulation works and why it matters, the Second Edition expands coverage on static simulation and the applications of spreadsheets to perform simulation. The new edition also introduces the use of the open source statistical package, R, for both performing statistical testing and fitting distributions. In addition, the models are presented in a clear and precise pseudo-code form, which aids in understanding and model communication. Simulation Modeling and Arena, Second Edition also features: Updated coverage of necessary statistical modeling concepts such as confidence interval construction, hypothesis testing, and parameter estimation Additional examples of the simulation clock within discrete event simulation modeling involving the mechanics of time advancement by hand simulation A guide to the Arena Run Controller, which features a debugging scenario New homework problems that cover a wider range of engineering applications in transportation, logistics, healthcare, and computer science A related website with an Instructor’s Solutions Manual, PowerPoint® slides, test bank questions, and data sets for each chapter Simulation Modeling and Arena, Second Edition is an ideal textbook for upper-undergraduate and graduate courses in modeling and simulation within statistics, mathematics, industrial and civil engineering, construction management, business, computer science, and other departments where simulation is practiced. The book is also an excellent reference for professionals interested in mathematical modeling, simulation, and Arena.

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers

Nahmias and Olsen skillfully blend comprehensive coverage of topics with careful integration of mathematics. The authors’ decades of experience in the field contributed to the success of previous editions; the eighth edition continues the long tradition of excellence. Clearly written, reasonably priced, with an abundance of expertly formulated practice problems and updated examples, this textbook is essential reading for analyzing and improving all facets of operations. Some of the material in the newest edition has been reorganized. For example, the first chapter introduces service strategy, the product/process matrix and flexible manufacturing systems, benchmarking, the productivity frontier, the innovation curve, and lean production as a strategy. The focus is slightly more international. The analysis of capacity growth planning now appears in the chapter on supply chain analytics. Aggregate planning details were added to chapter 3, including chase and level strategies in an appendix to the chapter. There is an expanded discussion on risk pooling in the chapter on supply chain strategy. The mechanics behind lean production are included in the chapter on push and pull production systems. The chapter on quality and assurance downplays sampling in favor of discussions of quality management, process capability, and the waste elimination side of lean. The separate chapter on facilities layout and location was eliminated and the information redistributed throughout the text. The authors reinforce the learning process through key points at the beginning of each chapter to guide the reader, snapshots that provide useful examples of applications to businesses, and historical notes that provide a context for the topics discussed. Production and Operations Analytics, 8/e provides the tools for adapting to the dynamic global marketplace.