制造资源驱动的产业集群订单分配研究

针对集群制造资源利用不均衡现象,在对集群内供应商进行综合评价的基础上,提出了以生产负荷率均衡和制造资源综合性能最优为决策准则的订单分配方法,在考虑供应商制造资源利用状况的同时兼顾了所选用制造资源的性能;建立了订单分配多目标规划模型,并利用基于模糊逻辑的遗传算法对模型进行求解;最后通过实例验证了算法的有效性.结果表明:提出的模型和算法能够获得满意的解.     

权值动态分配的GFSINS多角速度加权平均融合算法

针对单一角速度算法解算精度不高,提出将最优加权平均法应用于GFSINS角速度解算中。针对实际应用中各种算法无法准确获取到角速度解算误差方差的情况,给出了一种对方差进行实时估计,再基于最优权值分配原则来动态分配权值的加权融合算法;对积分法、开方法、微分法和对数法四种角速度算法进行了有效融合,并完成了仿真。仿真结果表明,即使精度最低的积分法参与加权融合,也能进一步提高融合精度,同时还验证了加权平均法在系统角速度解算中的有效性,融合后,角速度精度比对数法提高了一倍。     

A value for multichoice games

A multichoice game is a generalization of a cooperative TU game in which each player has several activity levels. We study the solution for these games proposed by Van Den Nouweland et al. (1995) [Van Den Nouweland, A., Potters, J., Tijs, S., Zarzuelo, J.M., 1995. Cores and related solution concepts for multi-choice games. ZOR-Mathematical Methods of Operations Research 41, 289–311]. We show that this solution applied to the discrete cost sharing model coincides with the Aumann-Shapley method proposed by Moulin (1995) [Moulin, H., 1995. On additive methods to share joint costs. The Japanese Economic Review 46, 303–332]. Also, we show that the Aumann-Shapley value for continuum games can be obtained as the limit of multichoice values for admissible convergence sequences of multichoice games. Finally, we characterize this solution by using the axioms of balanced contributions and efficiency.     

Efficient Coordination by Optimal Allocation of Decision Rights for Participants on Electronic Financial Services Markets

Information technology (IT) is enabling large companies and particularly banking firms to create new forms of organizations. Both globalization of markets and stronger regulation throughout the world puts pressure on banking firms to either spend more money coordinating business activities in the traditional hierarchical ways or to employ new forms of organizations enabled by (lower costs of) IT. When facing uncertain demand in multiple horizontal markets, resource allocation problems occur. Accordingly, the location of decision authority in a multilevel hierarchical organization has profound impact on the performance of the firm. The firm has to design its coordination structure, which determines who makes the resource allocation decisions. Considering the tradeoff between pooling effects in the case of centralized decision-making and better assessment of local markets in the case of decentralized decision-making, the decision problem where to locate decision rights to maximize total profits has to be solved. In this paper we investigate for both independent and dependent demands the total profits for each of the possible coordination mechanisms: centralized decision-making, decentralized decision-making, and intermediate-level decision-making. It turns out that—depending on the crucial parameters of the firm—decentralized decision-making or centralized decision-making may be optimal. But in many relevant cases the optimal location of decision rights is at an intermediate level of the hierarchy. We illustrate the findings by considering the banking firm coordinating equity capital allocation by granting alternative decision rights to their employees as participants on electronic financial markets. Finally we discuss the generality of the approach and its applicability in other areas such as inventory management.     

Multi-channel sensing and resource allocation in energy constrained cognitive radio networks

We consider a cognitive radio network in a multi-channel licensed environment. Secondary user transmits in a channel if the channel is sensed to be vacant. This results in a tradeoff between sensing time and transmission time. When secondary users are energy constrained, energy available for transmission is less if more energy is used in sensing. This gives rise to an energy tradeoff. For multiple primary channels, secondary users must decide appropriate sensing time and transmission power in each channel to maximize average aggregate-bit throughput in each frame duration while ensuring quality-of-service of primary users. Considering time and energy as limited resources, we formulate this problem as a resource allocation problem. Initially a single secondary user scenario is considered and solution is obtained using decomposition and alternating optimization techniques. Later we extend the analysis for the case of multiple secondary users. Simulation results are presented to study effect of channel occupancy, fading and energy availability on performance of proposed method.     

An adaptive step-size spectrum auction mechanism for two-tier heterogeneous networks

Recently, with the rapid growth of demands for wireless communications, dynamic spectrum allocation is one of the key technologies in cognitive radio networks to resolve the realistic problem of low utilization efficiency of spectrum. It mainly focuses on how the spectrum owner dynamically allocates idle spectrum to secondary users who have no licensed spectrum for communications. In this paper, a dynamic spectrum allocation model based on auction theory in a two-tier heterogeneous network is proposed, in which the primary users (PUs) are the sellers, the central processor (CP) auctioneer is the coordinator, and femtocell base station (FBS) as the buyer bids for the idle spectrum and act as a wireless access point that provides communication services for secondary users (SUs). Its basic process is as follows: the auctioneer gradually raises the spectrum price from the reserved price; each bidder decides whether participates in the purchase or not. It is characterized by distributed execution and low complexity which can reduce unnecessary information exchange between primary users or secondary users. Meanwhile it can enhance the utilization of spectrum and improve the efficiency of the auction by generate the incentive mechanism.     

大数据云中心虚拟机资源高效分配应用研究

为降低大数据云中心的能量消耗和实现资源的优化配置,提出一种虚拟机资源高效分配策略。 提出的策略对选定的特征上具备相似性任务分组的聚类进行定义,将各组任务映射到定制化的高效虚拟机类型。其高效指的是以最低限度的资源损耗成功执行任务。虚拟机的相关参数为核数量、内存量和存储量。虚拟机分配基于日志中提取的历史数据,并以任务的使用模式为基础。提出的资源分配策略以任务的实际资源使用量为基础,实现了能源消耗的降低。实验结果表明：不同聚类任务下,提出的虚拟机资源分配策略可以大幅节约能源消耗,具有较低的平均任务拒绝次数。     

数字化机步旅抢修任务动态调度框架研究

针对一体化机动进攻作战中战场抢修任务动态分配缺乏定量化确定方法的问题,对数字化机步旅抢修任务动态调度的框架结构进行了研究。借鉴Hall三维结构方法论,从对象维、过程维和技术维3个维度建立了抢修任务动态调度的框架结构,并以此为基础,分析梳理出了抢修任务动态调度的7个核心子问题,总结了这些核心子问题的自身特性,为抢修任务动态调度的后续研究提供了宏观规划和微观指导。     

基于泊位偏好与岸桥干扰的泊位和岸桥分配

泊位和岸桥是集装箱港口资源中最紧缺的资源,合理的泊位分配和岸桥调度可以提高集装箱港口的资源利用率和港口的运作效率和效益。针对泊位偏离和岸桥工作损失两个因素,文章建立了集装箱港口泊位和岸桥的混合整数线性规划模型;运用采集自宁波某典型集装箱港口的数据,用Gurobi优化软件和两阶段启发式算法对模型进行了求解;对计算结果进行了经济性分析。计算结果表明:该港口的岸线资源利用率为46%时,1000m~1600m基本没被利用;18台岸桥要比16台岸桥的目标值更优,求解时间更短,而且18台岸桥的平均利用率为80%,为此,建议该港口再增加两台岸桥。同时发现:随着船舶规模的增加,Gurobi优化求解的时间增长较快,而两阶段启发式算法仍能在很短时间内求得准优解。     

考虑存在取消预约情形的门诊预约能力分配策略

在现实的门诊预约问题中,已经预约的患者在接收医疗服务之前,有可能取消先前的预约,这会对医院的收益造成负面影响,如何在考虑患者存在取消预约的情形下,设计合理有效的能力分配策略来保证医院的收益,是一个值得研究的问题.本文针对具有提前预约和当天预约的门诊预约能力分配问题,在考虑提前预约患者可能存在取消预约行为的情形下,提出了一种提前预约患者和当天预约患者的最优能力分配策略。文中首先以医院的期望收益最大作为决策目标,建立了存在取消预约患者的医疗预约问题的马尔科夫过程模型,并给出了该模型的相关性质;基于所建立模型的特征,证明了对于任意的提前预约时段,存在提前预约患者的最佳数量,进而给出了提前预约患者和当天预约患者的最优能力分配策略以及确定该策略的精确算法;最后,通过数值试验说明了本文所提出的能力分配策略的适用性和有效性。