A randomized parallel branch-and-bound procedure

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Abstract
We present a universal randomized method called Local Best-First Search for parallelizing sequential branch-and-bound algorithms. The method executes on a message-passing multiprocessor system, and requires no global data structures or complex communication protocols. We show that, uniformly on all instances, the execution time of the method is unlikely to exceed a certain inherent lower bound by more than a constant factor.

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