Fast Hybrid Computer Implementation of the Dynostat Algorithm

Abstract
In optimal resource allocation problems the Dynostat algorithm separates the overall optimization task into less complicated optimum seeking techniques working in parallel. A hybrid computer implementation is shown to provide a much faster optimizer than was previously the case using a digital computer. Solution accuracies are considered adequate for many practical applications. The improved formulation presented of gradient search is advantageous for high-speed optimization. Confidence is increased in analog computer solutions by introducing auxiliary algorithms that check on solution feasibility and also improve accuracy.

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