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作 者:张帆[1] 邵之江[1] 仲卫涛[1] 钱积新[1]
机构地区:[1]浙江大学系统工程研究所,浙江杭州310027
出 处:《化工学报》2001年第5期391-400,共10页CIESC Journal
基 金:国家自然科学基金资助项目 !(No .2 990 60 10 )&&
摘 要:针对大规模化工过程系统优化计算能力不够的情况 ,讨论用机群系统建构成并行优化计算环境 .在分析并行计算的原理和现状后 ,对优化算法的并行化进行探讨 ,并且深入讨论了大规模优化算法SQP的并行化和如何提高机群系统效率的问题 .通过精馏塔优化算例 。Current trends toward increased model detail and rigorous optimization of chemical process accelerate the need to solve very large systems.Even with the high performance computers nowadays,there still exists many difficulties for a single computer to solve large-scale chemical process optimization problems.In this paper,parallel computing and algorithms for chemical process optimization problems are reviewed.Details of cluster of workstations,a relatively recen development,are given to highlight its advantages compared with other approaches in parallel computing.As SQP has emerged as the algorithm of choice for solving large-scale chemical process optimization problems,several parallel strategies for SQP are also presented.Finally,a parallel strategy utilizing cluster of workstations is proposed to solve chemical process optimization problems efficiently.Observations indicate that the degree of granularity plays a major role in this approach.It should be carefully schemed to balance the load of communication and the distributed calculation steps.Computing results on a distillation column optimization problem demonstrate the efficiency of this approach.
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