The PEGS-rule for probabilistic sequencing situations

This paper considers one-machine sequencing situations in which agents are uncertain about the initial order before the processing of the machine starts. The agents are allowed to rearrange positions to save costs w.r.t. the possible initial orders. For these sequencing situations we introduce and characterize in two different ways the Probabilistic Equal Gain Splitting (PEGS) rule that assigns the expected cost savings to the agents.