  In this paper we analyze the worst-case performance of a greedy algorithm
called Largest-Z-ratio-First for the problem of scheduling unreliable jobs on m
parallel machines. Each job is characterized by a success probability and a
reward earned in the case of success. In the case of failure, the jobs
subsequently sequenced on that machine cannot be performed. The objective is to
maximize the expected reward. We show the algorithm provides an approximation
ratio of approximately 0.853196, and that the bound is tight.
