This book addresses the problem of the uncertainty of processing time in a stochastic environment.Stochastic scheduling is in the area of production scheduling. 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.Stochastic scheduling is in the area of production scheduling. 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.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.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 dil“Y