Ordinal On-Line Scheduling for Maximizing the Minimum Machine Completion Time.

This paper considers the on-line problem of scheduling nonpreemptively n independent jobs on m > 1 identical and parallel machines with the objective to maximize the minimum machine completion time. It is assumed that the values of the processing times are unknown but the order of the jobs by their processing times is known in advance. We are asked to decide the assignment of all the jobs to some machines at time zero by utilizing only ordinal data rather than the actual magnitudes of jobs. Algorithms to slove the problem are called ordinal algorithms. In this paper, we give lower bounds and ordinal algorithms. We first propose an algorithm MIN which is at most $$(\left\lceil {\sum {_{i = 1}^m {\text{ }}1/} i} \right\rceil + 1)$$ -competitive for any m machine case, while the lower bound is ∑ 1/i. Both are on the order of Θ(ln m). Furthermore, for m = 3, we present an optimal algorithm. [ABSTRACT FROM AUTHOR]