大规模设计的英文
massive design
例句与用法
- Abstract : a new method , collaborative allocation ( ca ) , is proposed to solve the large - scale optimum allocation problem in aircraft conceptual design . according to the characteristics of optimum allocation in aircraft conceptual design . the principle and mathematical model of ca are established . the optimum allocation problem is decomposed into one main optimization problem and several sub - optimization problems . a group of design requirements for subsystems are provided by the main system respectively , and the subsystems execute their own optimizations or further provide the detailed design requirements to the bottom components of aircraft , such as spars , ribs and skins , etc . the subsystems minimize the discrepancy between their own local variables and the corresponding allocated values , and then return the optimization results to main optimization . the main optimization is performed to reallocate the design requirements for improving the integration performance and progressing toward the compatibilities among subsystems . ca provides the general optimum allocation architecture and is easy to be carried out . furthermore , the concurrent computation can also be realized . two examples of optimum reliability allocation are used to describe the implementation procedure of ca for two - level allocation and three - level allocation respectively , and to validate preliminarily its correctness and effectiveness . it is shown that the developed method can be successfully used in optimum allocation of design requirements . then taking weight requirement allocation as example , the mathematical model and solution procedure for collaborative allocation of design requirements in aircraft conceptual design are briefly depicted
文摘:探讨了一种新的设计指标最优分配方法- -协同分配法,用于处理飞机顶层设计中的大规模设计指标最优分配问题.分析了飞机顶层设计中的设计指标最优分配特征,据此给出了协同法的原理并建立了数学模型.协同法按设计指标分配关系将最优分配问题分解为主系统优化和子系统优化,主优化对子系统设计指标进行最优分配,子优化以最小化分配设计指标值与期望设计指标值之间的差异为目标,进行子系统最优设计,或对底层元件(如飞机翼梁、翼肋和翼盒等)进行设计指标最优分配,并把最优解信息反馈给主优化.主优化通过子优化最优解信息构成的一致性约束协调分配量,提高系统整体性能,并重新给出分配方案.主系统与子系统反复协调,直到得到设计指标最优分配方案.两层可靠度指标分配算例初步验证了本文方法的正确性与可行性,三层可靠度指标分配算例证明了本文方法的有效性.最后,以重量指标分配为例,简要叙述了针对飞机顶层设计中设计指标协同分配的数学模型和求解思路 - A new method , collaborative allocation ( ca ) , is proposed to solve the large - scale optimum allocation problem in aircraft conceptual design . according to the characteristics of optimum allocation in aircraft conceptual design . the principle and mathematical model of ca are established . the optimum allocation problem is decomposed into one main optimization problem and several sub - optimization problems . a group of design requirements for subsystems are provided by the main system respectively , and the subsystems execute their own optimizations or further provide the detailed design requirements to the bottom components of aircraft , such as spars , ribs and skins , etc . the subsystems minimize the discrepancy between their own local variables and the corresponding allocated values , and then return the optimization results to main optimization . the main optimization is performed to reallocate the design requirements for improving the integration performance and progressing toward the compatibilities among subsystems . ca provides the general optimum allocation architecture and is easy to be carried out . furthermore , the concurrent computation can also be realized . two examples of optimum reliability allocation are used to describe the implementation procedure of ca for two - level allocation and three - level allocation respectively , and to validate preliminarily its correctness and effectiveness . it is shown that the developed method can be successfully used in optimum allocation of design requirements . then taking weight requirement allocation as example , the mathematical model and solution procedure for collaborative allocation of design requirements in aircraft conceptual design are briefly depicted
探讨了一种新的设计指标最优分配方法- -协同分配法,用于处理飞机顶层设计中的大规模设计指标最优分配问题.分析了飞机顶层设计中的设计指标最优分配特征,据此给出了协同法的原理并建立了数学模型.协同法按设计指标分配关系将最优分配问题分解为主系统优化和子系统优化,主优化对子系统设计指标进行最优分配,子优化以最小化分配设计指标值与期望设计指标值之间的差异为目标,进行子系统最优设计,或对底层元件(如飞机翼梁、翼肋和翼盒等)进行设计指标最优分配,并把最优解信息反馈给主优化.主优化通过子优化最优解信息构成的一致性约束协调分配量,提高系统整体性能,并重新给出分配方案.主系统与子系统反复协调,直到得到设计指标最优分配方案.两层可靠度指标分配算例初步验证了本文方法的正确性与可行性,三层可靠度指标分配算例证明了本文方法的有效性.最后,以重量指标分配为例,简要叙述了针对飞机顶层设计中设计指标协同分配的数学模型和求解思路 - Abstract : an algorithm is presented for better legal solution in detailed placement of large scale mixed macros and standard cells ic design . due to the limitation of computing complexity , an effective and efficient initial placement is very important for detailed placement . novelty of this algorithm lies in a better solution at initial stage by using network - flow method to satisfy row capacity constraint and the thought of linear placement problem ( lpp ) to resolve overlaps . moreover , divide - and - conquer strategy and other simplified methods are adopted to minimize complexity . experimental results show that the algorithm can get an average of 16 wire length improvement on paflo in reasonable cpu time
文摘:以大规模混合模式布局问题为背景,提出了有效的初始详细布局算法.在大规模混合模式布局问题中,由于受到计算复杂性的限制,有效的初始布局算法显得非常重要.该算法采用网络流方法来满足行容量约束,采用线性布局策略解决单元重叠问题.同时,为解决大规模设计问题,整体上采用分治策略和简化策略,有效地控制问题的规模,以时间开销的少量增加换取线长的明显改善.实验结果表明该算法能够取得比较好的效果,平均比paflo算法有16的线长改善,而cpu计算时间只有少量增加
