Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain an...Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain and the general-director chain,to handle the trade-off between technical and management decisions. However, previous works on organization search have mainly focused on the single-chain hierarchical organization in which all decisions are regarded as homogeneous. The heterogeneity and the interdependency between technical decisions and management decisions have been neglected. A two-chain hierarchical organization structure mapped from a real complex project is constructed. Then, a discrete decision model for a Liang Zong two-chain hierarchical organization in an NK model framework is proposed. This model proves that this kind of organization structure can reduce the search space by a large amount and that the search process should reach a final stable state more quickly. For a more complicated decision mechanism, a multi-agent simulation based on the above NK model is used to explore the effect of the two-chain organization structure on the speed, stability, and performance of the search process. The results provide three insights into how, compared with the single-chain hierarchical organization, the two-chain organization can improve the search process: it can reduce the number of iterations efficiently; the search is more stable because the search space is a smoother hill-like fitness landscape; in general, the search performance can be improved.However, when the organization structure is very complicated, the performance of a two-chain organization is inferior to that of a single-chain organization. These findings about the efficiency of the unique Chinese-style organization structure can be used to guide organization design for complex projects.展开更多
Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical app...Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments. Firstly, the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler. Then, the hierarchical resource allocation approach is presented in two levels. At the platform level, a task assignment algorithm based on genetic simulated annealing （GSA） is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups, so that resources can be allocated as partitions and mapped to task groups. While yielding to all the resource con- straints, the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load. At the node level, partition parameters are optimized, so that the computational resource can be allocated further. An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity. Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presented in the context of task assignment in IMA systems.展开更多
To solve the problem such as too many models, long computing time and so on, a hierarchical multiple models direct adaptive decoupling controller is designed. It consists of multiple levels. In the upper level, the be...To solve the problem such as too many models, long computing time and so on, a hierarchical multiple models direct adaptive decoupling controller is designed. It consists of multiple levels. In the upper level, the best model is chosen according to the switching index. Then multiple fixed models are constructed on line to cover the region which the above chosen fixed model lies in.In the last level, one free-running and one re-initialized adaptive model are added to guarantee the stability and improve the transient response. By selection of the weighting polynomial matrix, it not only eliminates the steady output error and places the poles of the closed loop system arbitrarily, but also decouples the system dynamically. At last, for this multiple models switching system, global convergence is obtained under common assumptions. Compared with the conventional multiple models adaptive controller, it reduces the number of the fixed models greatly. If the same number of the fixed models is used, the system transient response and decoupling result are improved. The simulation example illustrates the power of the derived controller.展开更多
A class of large-scale systems, where the overall objective function is a nonlinear function of performance index of each subsystem, is investigated in this paper. This type of large-scale control problem is non-separ...A class of large-scale systems, where the overall objective function is a nonlinear function of performance index of each subsystem, is investigated in this paper. This type of large-scale control problem is non-separable in the sense of conventional hierarchical control. Hierarchical control is extended in the paper to large-scale non-separable control problems, where multiobjective optimization is used as separation strategy. The large-scale non-separable control problem is embedded, under certain conditions, into a family of the weighted Lagrangian formulation. The weighted Lagrangian formulation is separable with respect to subsystems and can be effectively solved using the interaction balance approach at the two lower levels in the proposed three-level solution structure. At the third level, the weighting vector for the weighted Lagrangian formulation is adjusted iteratively to search the optimal weighting vector with which the optimal of the original large-scale non-separable control problem is obtained. Theoretical base of the algorithm is established. Simulation shows that the algorithm is effective.展开更多
针对采用分布式并行方法仿真WLAN(wireless local area network)场景时存在的随终端节点个数增加而效率降低的问题,提出了一种面向WLAN的分布式分层并行仿真方法。基于WLAN的星状网络拓扑结构,令仿真接入节点的进程为主进程,负责WLAN全...针对采用分布式并行方法仿真WLAN(wireless local area network)场景时存在的随终端节点个数增加而效率降低的问题,提出了一种面向WLAN的分布式分层并行仿真方法。基于WLAN的星状网络拓扑结构,令仿真接入节点的进程为主进程,负责WLAN全网中其他仿真节点的时间同步;将所有仿真终端节点的进程均匀分为若干组,由组长负责该组内进程的同步。在主进程广播仿真开始事件后,组长进程先收集本组组员终端节点推进结束消息,当收齐后再向主进程汇报。形成“主进程-组长进程-组员进程”的3层分层结构。在不同计算负荷下,仿真分析并得到了分层仿真方法的时间增益因子闭合表达式。仿真结果表明,与现有不分层的仿真方法相比,当平均计算负荷为1.2倍单位时长、节点个数为100时,所提分层仿真方法的增益可达50%。展开更多
基金supported by the National Natural Science Foundation of China(7157105771390522)the Key Lab for Public Engineering Audit of Jiangsu Province,Nanjing Audit University(GGSS2016-08)
文摘Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain and the general-director chain,to handle the trade-off between technical and management decisions. However, previous works on organization search have mainly focused on the single-chain hierarchical organization in which all decisions are regarded as homogeneous. The heterogeneity and the interdependency between technical decisions and management decisions have been neglected. A two-chain hierarchical organization structure mapped from a real complex project is constructed. Then, a discrete decision model for a Liang Zong two-chain hierarchical organization in an NK model framework is proposed. This model proves that this kind of organization structure can reduce the search space by a large amount and that the search process should reach a final stable state more quickly. For a more complicated decision mechanism, a multi-agent simulation based on the above NK model is used to explore the effect of the two-chain organization structure on the speed, stability, and performance of the search process. The results provide three insights into how, compared with the single-chain hierarchical organization, the two-chain organization can improve the search process: it can reduce the number of iterations efficiently; the search is more stable because the search space is a smoother hill-like fitness landscape; in general, the search performance can be improved.However, when the organization structure is very complicated, the performance of a two-chain organization is inferior to that of a single-chain organization. These findings about the efficiency of the unique Chinese-style organization structure can be used to guide organization design for complex projects.
基金supported by the National Natural Science Foundation of China (60879024)
文摘Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments. Firstly, the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler. Then, the hierarchical resource allocation approach is presented in two levels. At the platform level, a task assignment algorithm based on genetic simulated annealing （GSA） is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups, so that resources can be allocated as partitions and mapped to task groups. While yielding to all the resource con- straints, the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load. At the node level, partition parameters are optimized, so that the computational resource can be allocated further. An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity. Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presented in the context of task assignment in IMA systems.
基金Supported by the National "863" High Technology Project (2002AA412130)Natural Science Foundation of P. R. China (60474051)
文摘To solve the problem such as too many models, long computing time and so on, a hierarchical multiple models direct adaptive decoupling controller is designed. It consists of multiple levels. In the upper level, the best model is chosen according to the switching index. Then multiple fixed models are constructed on line to cover the region which the above chosen fixed model lies in.In the last level, one free-running and one re-initialized adaptive model are added to guarantee the stability and improve the transient response. By selection of the weighting polynomial matrix, it not only eliminates the steady output error and places the poles of the closed loop system arbitrarily, but also decouples the system dynamically. At last, for this multiple models switching system, global convergence is obtained under common assumptions. Compared with the conventional multiple models adaptive controller, it reduces the number of the fixed models greatly. If the same number of the fixed models is used, the system transient response and decoupling result are improved. The simulation example illustrates the power of the derived controller.
文摘A class of large-scale systems, where the overall objective function is a nonlinear function of performance index of each subsystem, is investigated in this paper. This type of large-scale control problem is non-separable in the sense of conventional hierarchical control. Hierarchical control is extended in the paper to large-scale non-separable control problems, where multiobjective optimization is used as separation strategy. The large-scale non-separable control problem is embedded, under certain conditions, into a family of the weighted Lagrangian formulation. The weighted Lagrangian formulation is separable with respect to subsystems and can be effectively solved using the interaction balance approach at the two lower levels in the proposed three-level solution structure. At the third level, the weighting vector for the weighted Lagrangian formulation is adjusted iteratively to search the optimal weighting vector with which the optimal of the original large-scale non-separable control problem is obtained. Theoretical base of the algorithm is established. Simulation shows that the algorithm is effective.
文摘针对采用分布式并行方法仿真WLAN(wireless local area network)场景时存在的随终端节点个数增加而效率降低的问题,提出了一种面向WLAN的分布式分层并行仿真方法。基于WLAN的星状网络拓扑结构,令仿真接入节点的进程为主进程,负责WLAN全网中其他仿真节点的时间同步;将所有仿真终端节点的进程均匀分为若干组,由组长负责该组内进程的同步。在主进程广播仿真开始事件后,组长进程先收集本组组员终端节点推进结束消息,当收齐后再向主进程汇报。形成“主进程-组长进程-组员进程”的3层分层结构。在不同计算负荷下,仿真分析并得到了分层仿真方法的时间增益因子闭合表达式。仿真结果表明,与现有不分层的仿真方法相比,当平均计算负荷为1.2倍单位时长、节点个数为100时,所提分层仿真方法的增益可达50%。
