Expectation-Variance Analysis of a Schedule
$60.00 ( ) USD
- Subhash C. Sarin, Virginia Polytechnic Institute and State University
- Balaji Nagarajan
- Lingrui Liao
$60.00 USD ( )
Adobe eBook Reader
Looking for an examination copy?
If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact firstname.lastname@example.org providing details of the course you are teaching.
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 Web site for ease of student and user implementation.Read more
- Computer software containing the algorithms is provided on an accompanying website for ease of student and user implementation
- Analyzes variability of a schedule, in a stochastic environment, where the processing time of a job is not known with certainty
- This text presents algorithms to determine variability of a schedule under various machine configurations and objective functions
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: June 2010
- format: Adobe eBook Reader
- isbn: 9780511764073
- contains: 30 b/w illus. 43 tables
- availability: Adobe Reader ebooks available from eBooks.com
Table of Contents
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.
Welcome to the resources site
Here you will find free-of-charge online materials to accompany this book. The range of materials we provide across our academic and higher education titles are an integral part of the book package whether you are a student, instructor, researcher or professional.
Find resources associated with this titleYour search for '' returned .
Type Name Unlocked * Format Size
*This title has one or more locked files and access is given only to instructors adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you either need first to sign in or register for an account.
These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.
If you are having problems accessing these resources please email email@example.com
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email firstname.lastname@example.orgRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×