Bounds on optimal values in stochastic scheduling

Consistent stochastic orders of processing times and objective functions yield optimal policies in many stochastic scheduling problems. When these orders fail to hold, however, finding optimal values may be difficult. In this paper, we show how to bound these values in general situations including problems with unreliable machines and tardiness-based objectives.