Comparisons Between Deterministic And Stochastic Scheduling Problems With Release Dates And Due Dates

This volume contains the proceedings of an Advanced Study and Re search Institute on Theoretical Approaches to Scheduling Problems. The Institute was held in Durham, England, from July 6 to July 17, 1981. It was attended by 91 participants from fifteen different countries. The format of the Institute was somewhat unusual. The first eight of the ten available days were devoted to an Advanced Study Insti tute, with lectures on the state of the art with respect to deter ministic and stochastic scheduling models and on the interface between these two approaches. The last two days were occupied by an Advanced Research Institute, where recent results and promising directions for future research, especially in the interface area, were discussed. Altogether, 37 lectures were delivered by 24 lecturers. They have all contributed to these proceedings, the first part of which deals with the Advanced Study Institute and the second part of which covers the Advanced Research Institute. Each part is preceded by an introduction, written by the editors. While confessing to a natural bias as organizers, we believe that the Institute has been a rewarding and enjoyable event for everyone concerned. We are very grateful to all those who have contributed to its realization.

In this paper we consider stochastic scheduling models where all relevant data (like processing times, release dates, due dates, etc.) are independent random variables, exponentially distributed. We are interested in the computational complexity of determining optimal policies for these stochastic scheduling models. We give a number of examples of models in which the optimal policies can be determined by polynomial time algorithms while the deterministic counterparts of these models are NP-complete. We also give some examples of stochastic scheduling models for which there exists no polynomial time algorithm if P is not equal NP. (Author).

Dealing primarily with machine scheduling models, this three-part approach covers deterministic models, stochastic models and applications in the real world.

This volume contains the proceedings of an Advanced Study and Re search Institute on Theoretical Approaches to Scheduling Problems. The Institute was held in Durham, England, from July 6 to July 17, 1981. It was attended by 91 participants from fifteen different countries. The format of the Institute was somewhat unusual. The first eight of the ten available days were devoted to an Advanced Study Insti tute, with lectures on the state of the art with respect to deter ministic and stochastic scheduling models and on the interface between these two approaches. The last two days were occupied by an Advanced Research Institute, where recent results and promising directions for future research, especially in the interface area, were discussed. Altogether, 37 lectures were delivered by 24 lecturers. They have all contributed to these proceedings, the first part of which deals with the Advanced Study Institute and the second part of which covers the Advanced Research Institute. Each part is preceded by an introduction, written by the editors. While confessing to a natural bias as organizers, we believe that the Institute has been a rewarding and enjoyable event for everyone concerned. We are very grateful to all those who have contributed to its realization.

Researchers in management, industrial engineering, operations, and computer science have intensely studied scheduling for more than 50 years, resulting in an astounding body of knowledge in this field. Handbook of Scheduling: Algorithms, Models, and Performance Analysis, the first handbook on scheduling, provides full coverage of the most recent and advanced topics on the subject. It assembles researchers from all relevant disciplines in order to facilitate cross-fertilization and create new scheduling insights. The book comprises six major parts, each of which breaks down into smaller chapters: · Part I introduces materials and notation, with tutorials on complexity theory and algorithms for the minimization of makespan, total completion time, dual objectives, maximum lateness, the number of late jobs, and total tardiness. · Part II is devoted to classical scheduling problems. · Part III explores scheduling models that originate in computer science, operations research, and management science. · Part IV examines scheduling problems that arise in real-time systems, focusing on meeting hard deadline constraints while maximizing machine utilization. · Part V discusses stochastic scheduling and queueing networks, highlighting jobs that are not deterministic. · Part VI covers applications, discussing scheduling problems in airline, process, and transportation industries, as well as in hospitals and educational institutions.

An updated edition of the text that explores the core topics in scheduling theory The second edition of Principles of Sequencing and Scheduling has been revised and updated to provide comprehensive coverage of sequencing and scheduling topics as well as emerging developments in the field. The text offers balanced coverage of deterministic models and stochastic models and includes new developments in safe scheduling and project scheduling, including coverage of project analytics. These new topics help bridge the gap between classical scheduling and actual practice. The authors—noted experts in the field—present a coherent and detailed introduction to the basic models, problems, and methods of scheduling theory. This book offers an introduction and overview of sequencing and scheduling and covers such topics as single-machine and multi-machine models, deterministic and stochastic problem formulations, optimization and heuristic solution approaches, and generic and specialized software methods. This new edition adds coverage on topics of recent interest in shop scheduling and project scheduling. This important resource: Offers comprehensive coverage of deterministic models as well as recent approaches and developments for stochastic models Emphasizes the application of generic optimization software to basic sequencing problems and the use of spreadsheet-based optimization methods Includes updated coverage on safe scheduling, lognormal modeling, and job selection Provides basic coverage of robust scheduling as contrasted with safe scheduling Adds a new chapter on project analytics, which supports the PERT21 framework for project scheduling in a stochastic environment. Extends the coverage of PERT 21 to include hierarchical scheduling Provides end-of-chapter references and access to advanced Research Notes, to aid readers in the further exploration of advanced topics Written for upper-undergraduate and graduate level courses covering such topics as scheduling theory and applications, project scheduling, and operations scheduling, the second edition of Principles of Sequencing and Scheduling is a resource that covers scheduling techniques and contains the most current research and emerging topics.

Traditionally, the three most important manufacturing functions are process planning, scheduling, and due-date assignment, which are handled sequentially and separately.This book integrates these manufacturing processes and functions to increase global performance along with manufacturing and production cost savings. Integrated Process Planning, Scheduling, and Due-Date Assignment combines the most important manufacturing functions to use manufacturing resources better, reduce production costs, and eliminate bottlenecks with increased production efficiency. The book covers how the integration will help eliminate scheduling conflicts and how to adapt to irregular shop floor disturbances. It also explains how other elements, such as tardiness and earliness, are penalized and how prioritizing helps improve weight performance function. This book will draw the interest of professionals, students, and academicians in process planning, scheduling, and due-date assignment. It could also be supplemental material for manufacturing courses in industrial engineering and manufacturing engineering departments.