Stochastic scheduling /:
"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...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge ; New York :
Cambridge University Press,
2010.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "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"--Provided by publisher. |
| Physical Description: | 1 online resource (xii, 191 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 183-186) and index. |
| ISBN: | 9780511770234 0511770235 9780511778032 0511778031 1282653431 9781282653436 9786612653438 6612653434 |
Staff View
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| contents | Introduction -- Robust scheduling approaches to hedge against processing time uncertainty -- Expectation-variance analysis in stochastic multiobjective scheduling -- Single-machine models -- Flow shop models -- Job-shop models -- Parallel-machine models -- The case of general processing time distribution -- Concluding remarks. |
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| spelling | Sarin, Subhash Chander. Stochastic scheduling / Subhash C. Sarin, Balaji Nagarajan, Lingrui Liao. Cambridge ; New York : Cambridge University Press, 2010. 1 online resource (xii, 191 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier "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"--Provided by publisher. Includes bibliographical references (pages 183-186) and index. Introduction -- Robust scheduling approaches to hedge against processing time uncertainty -- Expectation-variance analysis in stochastic multiobjective scheduling -- Single-machine models -- Flow shop models -- Job-shop models -- Parallel-machine models -- The case of general processing time distribution -- Concluding remarks. Print version record. Production scheduling. http://id.loc.gov/authorities/subjects/sh85118098 Ordonnancement (Gestion) TECHNOLOGY & ENGINEERING Industrial Technology. bisacsh TECHNOLOGY & ENGINEERING Industrial Engineering. bisacsh BUSINESS & ECONOMICS Production & Operations Management. bisacsh Production scheduling fast Nagarajan, Balaji. Liao, Lingrui. has work: Stochastic scheduling (Text) https://id.oclc.org/worldcat/entity/E39PCFMWgDJV9dhpFtdDXykQRq https://id.oclc.org/worldcat/ontology/hasWork Print version: Sarin, Subhash Chander. Stochastic scheduling. Cambridge ; New York : Cambridge University Press, 2010 9780521518512 (DLC) 2010000032 (OCoLC)501396712 |
| spellingShingle | Sarin, Subhash Chander Stochastic scheduling / Introduction -- Robust scheduling approaches to hedge against processing time uncertainty -- Expectation-variance analysis in stochastic multiobjective scheduling -- Single-machine models -- Flow shop models -- Job-shop models -- Parallel-machine models -- The case of general processing time distribution -- Concluding remarks. Production scheduling. http://id.loc.gov/authorities/subjects/sh85118098 Ordonnancement (Gestion) TECHNOLOGY & ENGINEERING Industrial Technology. bisacsh TECHNOLOGY & ENGINEERING Industrial Engineering. bisacsh BUSINESS & ECONOMICS Production & Operations Management. bisacsh Production scheduling fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85118098 |
| title | Stochastic scheduling / |
| title_auth | Stochastic scheduling / |
| title_exact_search | Stochastic scheduling / |
| title_full | Stochastic scheduling / Subhash C. Sarin, Balaji Nagarajan, Lingrui Liao. |
| title_fullStr | Stochastic scheduling / Subhash C. Sarin, Balaji Nagarajan, Lingrui Liao. |
| title_full_unstemmed | Stochastic scheduling / Subhash C. Sarin, Balaji Nagarajan, Lingrui Liao. |
| title_short | Stochastic scheduling / |
| title_sort | stochastic scheduling |
| topic | Production scheduling. http://id.loc.gov/authorities/subjects/sh85118098 Ordonnancement (Gestion) TECHNOLOGY & ENGINEERING Industrial Technology. bisacsh TECHNOLOGY & ENGINEERING Industrial Engineering. bisacsh BUSINESS & ECONOMICS Production & Operations Management. bisacsh Production scheduling fast |
| topic_facet | Production scheduling. Ordonnancement (Gestion) TECHNOLOGY & ENGINEERING Industrial Technology. TECHNOLOGY & ENGINEERING Industrial Engineering. BUSINESS & ECONOMICS Production & Operations Management. Production scheduling |
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