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Besides scheduling problems for single and parallel machines and shop scheduling problems, the book covers advanced models involving due-dates, sequence dependent change-over times and batching. A discussion of multiprocessor task scheduling and problems with multi-purpose machines is accompanied by the methods used to solve such problems, such as polynomial algorithms, dynamic programming procedures, branch-and-bound algorithms and local search heuristics, and the whole is rounded off with an analysis of complexity issues.
This handbook provides full coverage of the most recent and advanced topics in scheduling, assembling researchers from all relevant disciplines to facilitate new insights. Presented in six parts, these experts provides introductory material, complete with tutorials and algorithms, then examine classical scheduling problems. Part 3 explores scheduling models that originate in areas such as computer science, operations research. The following section examines scheduling problems that arise in real-time systems. Part 5 discusses stochastic scheduling and queueing networks, and the final section discusses a range of applications in a variety of areas, from airlines to hospitals.
Focusing on theory and applications of scheduling, the applications are drawn primarily from production and manufacturing environments, but state principles that are relevant to other settings as well. The broad range of topics includes deterministic and stochastic models.
This updated edition offers an indispensable exposition on real-time computing, with particular emphasis on predictable scheduling algorithms. It introduces the fundamental concepts of real-time computing, demonstrates the most significant results in the field, and provides the essential methodologies for designing predictable computing systems used to support time-critical control applications. Along with an in-depth guide to the available approaches for the implementation and analysis of real-time applications, this revised edition contains a close examination of recent developments in real-time systems, including limited preemptive scheduling, resource reservation techniques, overload handling algorithms, and adaptive scheduling techniques. This volume serves as a fundamental advanced-level textbook. Each chapter provides basic concepts, which are followed by algorithms, illustrated with concrete examples, figures and tables. Exercises and solutions are provided to enhance self-study, making this an excellent reference for those interested in real-time computing for designing and/or developing predictable control applications.
This new edition of the well established text Scheduling - Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as significant scheduling problems that occur in the real world. It again includes supplementary material in the form of slide-shows from industry and movies that show 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. The references have been made completely up-to-date. Theoreticians and practitioners alike will find this book of interest. Graduate students in operations management, operations research, industrial engineering, and computer science will find the book an accessible and invaluable resource. Scheduling - Theory, Algorithms, and Systems will serve as an essential reference for professionals working on scheduling problems in manufacturing, services, and other environments. Reviews of third edition: This well-established text covers both the theory and practice of scheduling. The book begins with motivating examples and the penultimate chapter discusses some commercial scheduling systems and examples of their implementations." (Mathematical Reviews, 2009)
This book is a printed edition of the Special Issue " Algorithms for Scheduling Problems" that was published in Algorithms
Multiobjective Scheduling by Genetic Algorithms describes methods for developing multiobjective solutions to common production scheduling equations modeling in the literature as flowshops, job shops and open shops. The methodology is metaheuristic, one inspired by how nature has evolved a multitude of coexisting species of living beings on earth. Multiobjective flowshops, job shops and open shops are each highly relevant models in manufacturing, classroom scheduling or automotive assembly, yet for want of sound methods they have remained almost untouched to date. This text shows how methods such as Elitist Nondominated Sorting Genetic Algorithm (ENGA) can find a bevy of Pareto optimal solutions for them. Also it accents the value of hybridizing Gas with both solution-generating and solution-improvement methods. It envisions fundamental research into such methods, greatly strengthening the growing reach of metaheuristic methods. This book is therefore intended for students of industrial engineering, operations research, operations management and computer science, as well as practitioners. It may also assist in the development of efficient shop management software tools for schedulers and production planners who face multiple planning and operating objectives as a matter of course.
This book provides an in-depth presentation of algorithms for and complexity of open shop scheduling. Open shops allow operations of a job to be executed in any order, contrary to flow and job shops where the order is pre-specified. The author brings the field up to date with more emphasis on new and recent results, and connections with graph edge coloring and mathematical programming. The book explores applications to production and operations management, wireless network scheduling, and timetabling. The book is addressed to researchers, graduate students, and practitioners in Operations Research, Operations Management, computer science and mathematics, who are developing and using mathematical approaches to applications in manufacturing, services and distributed wireless network scheduling.
Many real-time systems rely on static scheduling algorithms. This includes cyclic scheduling, rate monotonic scheduling and fixed schedules created by off-line scheduling techniques such as dynamic programming, heuristic search, and simulated annealing. However, for many real-time systems, static scheduling algorithms are quite restrictive and inflexible. For example, highly automated agile manufacturing, command, control and communications, and distributed real-time multimedia applications all operate over long lifetimes and in highly non-deterministic environments. Dynamic real-time scheduling algorithms are more appropriate for these systems and are used in such systems. Many of these algorithms are based on earliest deadline first (EDF) policies. There exists a wealth of literature on EDF-based scheduling with many extensions to deal with sophisticated issues such as precedence constraints, resource requirements, system overload, multi-processors, and distributed systems. Deadline Scheduling for Real-Time Systems: EDF and Related Algorithms aims at collecting a significant body of knowledge on EDF scheduling for real-time systems, but it does not try to be all-inclusive (the literature is too extensive). The book primarily presents the algorithms and associated analysis, but guidelines, rules, and implementation considerations are also discussed, especially for the more complicated situations where mathematical analysis is difficult. In general, it is very difficult to codify and taxonomize scheduling knowledge because there are many performance metrics, task characteristics, and system configurations. Also, adding to the complexity is the fact that a variety of algorithms have been designed for different combinations of these considerations. In spite of the recent advances there are still gaps in the solution space and there is a need to integrate the available solutions. For example, a list of issues to consider includes: preemptive versus non-preemptive tasks, uni-processors versus multi-processors, using EDF at dispatch time versus EDF-based planning, precedence constraints among tasks, resource constraints, periodic versus aperiodic versus sporadic tasks, scheduling during overload, fault tolerance requirements, and providing guarantees and levels of guarantees (meeting quality of service requirements). Deadline Scheduling for Real-Time Systems: EDF and Related Algorithms should be of interest to researchers, real-time system designers, and instructors and students, either as a focussed course on deadline-based scheduling for real-time systems, or, more likely, as part of a more general course on real-time computing. The book serves as an invaluable reference in this fast-moving field.