Title: Optimization using higher order approximations and parallel processing
Abstract: The time associated with solving realistic optimization problems is greatly reduced by employing sequential approximate optimization techniques. First order techniques are most commonly employed since conventional wisdom suggests that too many exact function evaluations are necessary to justify higher order techniques. Parallel processing allows several computations to be performed simultaneously and makes the use of higher order approaches more attractive. In this paper, the efficiency of both first and second order approximations is investigated. Parallel processing concepts, which could be implemented on a cluster of workstations, are discussed. A test problem, based on frequency spacing of a composite laminate, is presented. Results indicate that significant time savings can be obtained using a combined sequential approximate optimization approach which utilizes benefits of both first and second order techniques and is implemented using parallel processing.
Publication Year: 1998
Publication Date: 1998-04-20
Language: en
Type: article
Indexed In: ['crossref']
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