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Spruill,
Marcus C.
Spruill,
Marcus C.
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ItemRandom Restarts in Global Optimization(Georgia Institute of Technology, 2009-12-07) Hu, X. ; Shonkwiler, Ronald W. ; Spruill, Marcus C.In this article we study stochastic multistart methods for global optimization, which combine local search with random initialization, and their parallel implementations. It is shown that in a minimax sense the optimal restart distribution is uniform. We further establish the rate of decrease of the ensemble probability that the global minimum has not been found by the nth iteration. Turning to parallelization issues, we show that under independent identical processing (iip), exponential speedup in the time to hit the goal bin normally results. Our numerical studies are in close agreement with these finndings.
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ItemApproximate Speedup by Independent Identical Processing(Georgia Institute of Technology, 1994-05) Hu, X. ; Shonkwiler, Ronald W. ; Spruill, Marcus C.In this paper we prove that for algorithms which proceed to the next state based on information available from the current state, identical independent parallel processing using stochastic multistart methods always yields a speedup in the expected time to hit a goal which is locally exponential in the number of processors.
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ItemMathematical sciences : optimal experimental designs(Georgia Institute of Technology, 1984) Spruill, Marcus C.
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ItemOptimal experimental designs(Georgia Institute of Technology, 1982) Spruill, Marcus C.
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ItemOptimum designs for second order processes with general linear means(Georgia Institute of Technology, 1979) Spruill, Marcus C.
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ItemOptimum designs when the basic observations are sample paths of a stochastic process(Georgia Institute of Technology, 1977) Spruill, Marcus C.