Statistically Assessing Distributed Computing Approaches

This paper investigates the solution of manufacturing scheduling problems using different distributed computing schemes. The focus of this paper is on determining the statistically significant effects of a distributed computer model with respect to elapsed solution time and the amount of problem space investigated. Statistical inferences are drawn with respect to the number of processors and how the problem is partitioned. The best combinations of the number of processors and partitioning schemes are presented with respect to problem scenario and size. Additionally, comparisons are made with respect to the performance of different configurations of the distributed computer model.