An interactive mathematical programming approach to multi-criterion optimization is developed, and then illustrated by an application to the aggregated operating problem of an academic department.
This paper analyzes the performance of a discrete‐event combat simulation executed on a parallel processor under control of the Time Warp Operating System. Time Warp is in a class of distributed simulation methods called Optimistic methods which have proven to be useful over a wide range of simulations. The combat simulation used for this performance study, called STB88, is a division‐corps model incorporating a number of different types of computations. The speed‐up for three versions of this model on the Caltech/JPL Mark III Hypercube and the BBN Butterfly parallel processors was measured relative to an efficient sequential execution of the same model on the same hardware. The results indicate that STB88 version 1 achieves a speed‐up of 28.6 on 60 Mark III processors, while STB88 version 2 achieves a speed‐up of 36.8 on 100 Butterfly processors. Version 3 of STB88 achieved a speed‐up of 38.5 on 128 Mark III processors. The versions differed only in their interface to Time Warp. On the Butterfly, the sequential execution completed in 2 hours, while the 100 processor execution completed in 3.2 minutes.
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