Includes bibliographical references (p. 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.

"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.