CAJ | 학술논문

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，证明利用机群系统开展并行优化是行之有效的.
침대대규모화공과정계통우화계산능력불구적정황，토론용궤군계통건구성병행우화계산배경.재분석병행계산적원리화현상후，대우화산법적병행화진행탐토，병차심입토론료대규모우화산법SQP적병행화화여하제고궤군계통효솔적문제.통과정류탑우화산례，증명이용궤군계통개전병행우화시행지유효적.
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.