Load Balancing in Hypercube Solution of Stochastic Optimization Problems
ORSA Journal on Computing · 1995 · Volume 7 · Issue 3
Abstract
In some stochastic optimization problems the error bounds computed for the expected optimum can be decreased through recursive divide-and-conquer methods based on partitioning the support of the random variables. Each generated partition from the divide-and-conquer process can be treated independently. This class of problems is therefore easy to parallelize, and we describe two parallel implementations of this divide-and-conquer algorithm applied to PERT. Our results indicate that parallel processing and divide-and-conquer are indeed feasible and efficient for problems of this type. The tests were done on an Intel iPSC/2 multicomputer with 16 nodes. INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
Keywords
load balancing, hypercubes, parallel divide-and-conquer, stochastic optimization, bounds, expected value
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