Subhash C. Sarin

Stochastic Scheduling (eBook, PDF)

Expectation-Variance Analysis of a Schedule

• Format: PDF

Produktbeschreibung

Stochastic scheduling is in the area of production scheduling. There is a dearth of work that analyzes the variability of schedules. In a stochastic environment, in which the processing time of a job is not known with certainty, a schedule is typically analyzed based on the expected value of a performance measure. This book addresses this problem and presents algorithms to determine the variability of a schedule under various machine configurations and objective functions. It is intended for graduate and advanced undergraduate students in manufacturing, operations management, applied mathematics, and computer science, and it is also a good reference book for practitioners. Computer software containing the algorithms is provided on an accompanying website for ease of student and user implementation.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 31. März 2010
• Englisch
• ISBN-13: 9780511764073
• Artikelnr.: 38193152

Autorenporträt

Dr Subhash Sarin earned his PhD at North Carolina State University in 1978. He has made research contributions in production scheduling, sequencing, applied mathematical programming, and analyzing and designing algorithms for the operational control of manufacturing systems. He is a member of the editorial board of the International Journal of Production Planning and Control. Currently, Dr Sarin is the Paul T. Norton Endowed Professor at Virginia Polytechnic Institute and State University's Grado Department of Industrial and Systems Engineering. He is also Director of the Electronics Manufacturing Research Laboratory there, which provides a facility to support research on semiconductors and the electronics industry.

Inhaltsangabe

1. Introduction
2. Robust scheduling approaches to hedge against processing time uncertainty
3. Expectation-variance analysis in stochastic multi-objective scheduling
4. Single machine models
5. Flow shop models
6. Job shop models
7. The case of general processing time distribution
8. Concluding remarks.