Beta-robust scheduling for single-machine systems with uncertain processing times

In scheduling environments with processing time uncertainty, system performance is determined by both the sequence in which jobs are ordered and the actual processing times of jobs. For these situations, the risk of achieving substandard system performance can be an important measure of scheduling effectiveness. To hedge this risk requires an explicit consideration of both the mean and the variance of system performance associated with alternative schedules, and motivates a beta-robustness objective to capture the likelihood that a schedule yields actual performance no worse than a given target level. In this paper we focus on beta-robust scheduling issues in single-stage production environments with uncertain processing times. We define a general beta-robust scheduling objective, formulate the beta-robust scheduling problem that results when job processing times are independent random variables and the performance measure of interest is the total flow time across all jobs, establish problem complexity, and develop exact and heuristic solution approaches. We then extend the beta-robust scheduling model to consider situations where the uncertainty associated with individual job processing times can be selectively controlled through resource allocation. Computational results are reported to demonstrate the efficiency and effectiveness of the solution procedures.