Randomized group up and down experiments

An up and down (U&D) procedure is a sequential experiment used in binary response trials for identifying the treatment corresponding to a prespecified probability of positive response. Recently, a group version of U&D procedures has been proposed whereby at each stage a group of units is treated at the same level and the number of observed positive responses determines the treatment assigned to the next group. The deterministic nature of this algorithm leads to some limitations that in this paper we propose to overcome by introducing a randomization mechanism. A broad class of randomized group U&D’s is presented, giving the conditions for targeting the treatment level of interest. In addition, we study how the properties of the design change as we vary the method of randomization within this general class and find randomization schemes which guarantee desirable results in terms of the asymptotic behavior of the experiment.     

Dynamics and chaos control of the self-sustained electromechanical device with and without discontinuity

In this paper, we consider the dynamics and chaos control of the self-sustained electromechanical device with and without discontinuity. The amplitude equations are derived in the general case using the harmonic balance method. The model without discontinuity is first considered. The effects of the amplitude of the parametric modulation and some particular coefficients are found in the response curves. The transition to chaotic behavior is found using numerical simulations of the equations of motion. We find that chaos appears in the model between the quasi-periodic and periodic orbits when the amplitude of the external excitation E₀ vary. An adaptive Lyapunov control strategy enables us to drive the system from the chaotic states to a targeting periodic orbit. The effects of elasticity and damping on the dynamics of the self-sustained electromechanical system are also derived.     

多对象多指标多级别模糊模式识别模型的构建

给出对象指标相对隶属度矩阵和标准指标值相对隶属度矩阵的建立方法;提出如何构建一种新的模糊模式识别模型.     

Likelihood robust optimization for data-driven problems

We consider optimal decision-making problems in an uncertain environment. In particular, we consider the case in which the distribution of the input is unknown, yet there is some historical data drawn from the distribution. In this paper, we propose a new type of distributionally robust optimization model called the likelihood robust optimization (LRO) model for this class of problems. In contrast to previous work on distributionally robust optimization that focuses on certain parameters (e.g., mean, variance, etc.) of the input distribution, we exploit the historical data and define the accessible distribution set to contain only those distributions that make the observed data achieve a certain level of likelihood. Then we formulate the targeting problem as one of optimizing the expected value of the objective function under the worst-case distribution in that set. Our model avoids the over-conservativeness of some prior robust approaches by ruling out unrealistic distributions while maintaining robustness of the solution for any statistically likely outcomes. We present statistical analyses of our model using Bayesian statistics and empirical likelihood theory. Specifically, we prove the asymptotic behavior of our distribution set and establish the relationship between our model and other distributionally robust models. To test the performance of our model, we apply it to the newsvendor problem and the portfolio selection problem. The test results show that the solutions of our model indeed have desirable performance.     

磁性靶向药物递送中铁磁流体的动力学建模

在所有人体内进行的药物递送技术中,磁性药物靶向递送治疗由于其非入侵性和高靶向性而成为主要的方法．磁性药物靶向递送是将药物装载到磁性纳米颗粒上,利用外部磁场使其移动并聚焦在靶部位的方法．该法能提高靶部位药物的浓度,降低药物对正常组织的毒副作用．尽管已经有不少磁性靶向药物递送的理论分析,但是很少有人研究磁流体在血管里的流体动力学模型．该文提出了一个数学模型来描述作为药物载体的铁磁流体在外磁场作用下,在血管里的流体动力学特性,并在模型中增加了磁场力以及由此产生的不对称应力,增加了磁性纳米颗粒在磁场作用下的角动量方程．由于运动方程的数学复杂性,通过保留数学模型里物理特性最显著项来获得工程近似．用计算流体力学（CFD）进行数值仿真,分析了铁磁流体在一个模拟动脉瘤血管的三维管道里的流动状况,来进一步理解铁磁流体的临床应用．仿真结果和动物实验相一致．分析结果对于磁性靶向药物递送的各种应用提供了可参考的数据．     

基于员工行为差异的元胞自动机演化模拟与机制设计

提出了企业员工的正行为、零行为和负行为概念,分析了员工中不同行为间的相互影响.对传统元胞自动机方法进行了改进,建立了基于员工传播性和保持性的元胞自动机模型,并对员工不同的初始比例、不同的行为传播性和保持性以及企业不同奖励和惩罚性政策下的员工行为演化进行了模拟,得到了一些合理和有益的结论,并对不同情形下的人员管理提供了针对性建议.     

Conditional targeting for communication

In this work we propose the use of a targeting method applied to chaotic systems in order to reach special trajectories that encode arbitrary sources of messages. One advantage of this procedure is to overcome dynamical constraints which impose limits in the amount of information that the chaotic trajectories can encode. Another advantage is the message decoding, practically instantaneous and independent of any special technique or algorithm. Furthermore, with this procedure, information can be transmitted with no errors due to bounded noise.     

Small and Large Time Scale Analysis of a Network Traffic Model

Empirical studies of the internet and WAN traffic data have observed multifractal behavior at time scales below a few hundred milliseconds. There have been some attempts to model this phenomenon, but there is no model to connect the small time scale behavior with behavior observed at large time scales of bigger than a few hundred milliseconds. There have been separate analyses of models for high speed data transmissions, which show that appropriate approximations to large time scale behavior of cumulative traffic are either fractional Brownian motion or stable Lévy motion, depending on the input rates assumed. This paper tries to bridge this gap and develops and analyzes a model offering an explanation of both the small and large time scale behavior of a network traffic model based on the infinite source Poisson model. Previous studies of this model have usually assumed that transmission rates are constant and deterministic. We consider a nonconstant, multifractal, random transmission rate at the user level which results in cumulative traffic exhibiting multifractal behavior on small time scales and self-similar behavior on large time scales.     

Robust controlling of chaotic behavior in supply chain networks

The supply chain network is a complex nonlinear system that may have a chaotic behavior. This network involves multiple entities that cooperate to meet customers demand and control network inventory. Although there is a large body of research on measurement of chaos in the supply chain, no proper method has been proposed to control its chaotic behavior. Moreover, the dynamic equations used in the supply chain ignore many factors that affect this chaotic behavior. This paper offers a more comprehensive modeling, analysis, and control of chaotic behavior in the supply chain. A supply chain network with a centralized decision-making structure is modeled. This model has a control center that determines the order of entities and controls their inventories based on customer demand. There is a time-varying delay in the supply chain network, which is equal to the maximum delay between entities. Robust control method with linear matrix inequality technique is used to control the chaotic behavior. Using this technique, decision parameters are determined in such a way as to stabilize network behavior.     

考虑患者止步行为的动态入院接收决策模型

大型公立医院病床供需矛盾日益突出,医院作为服务系统有必要考虑由于病床需求响应速度不及时而引起的患者策略性行为。针对患者到达时间的随机性与住院时长的不确定性,本文提出考虑患者止步行为的动态入院接收决策问题,制定了适用于可等待慢性病患者的入院接收决策方法,旨在提高患者的就医满意度,有效权衡多类患者的接收数量,降低由于科室响应速度过慢引发的患者止步频率。首先,本文对考虑患者止步行为的动态入院接收决策问题进行数学描述及符号定义;然后,对患者止步行为的影响因素进行分析并构建止步概率函数;进一步地,构建考虑患者止步行为的动态入院接收马尔可夫决策过程(MDP)模型,并针对模型特点设计值迭代算法,最后通过数值算例验证本文所提方法的可行性与有效性。     

Optimal selection of process mean for a stochastic inventory model

It is very common to assume deterministic demand in the literature of integrated targeting – inventory models. However, if variability in demand is high, there may be significant disruptions from using the deterministic solution in probabilistic environment. Thus, the model would not be applicable to real world situations and adjustment must be made. The purpose of this paper is to develop a model for integrated targeting – inventory problem when the demand is a random variable. In particular, the proposed model jointly determines the optimal process mean, lot size and reorder point in (Q, R) continuous review model. In order to investigate the effect of uncertainty in demand, the proposed model is compared with three baseline cases. The first of which considers a hierarchical model where the producer determines the process mean and lot-sizing decisions separately. This hierarchical model is used to show the effect of integrating the process targeting with production/inventory decisions. Another baseline case is the deterministic demand case which is used to show the effect of variation in demand on the optimal solution. The last baseline case is for the situation where the variation in the filling amount is negligible. This case demonstrates the sensitivity of the total cost with respect to the variation in the process output. Also, a procedure is developed to determine the optimal solution for the proposed models. Empirical results show that ignoring randomness in the demand pattern leads to underestimating the expected total cost. Moreover, the results indicate that performance of a process can be improved significantly by reducing its variation.     

考虑顾客便利半径和质量阈值的竞争设施选址问题

在竞争设施选址问题中,顾客选择行为是决定设施占领市场份额的重要因素,其描述了需求在设施之间的分配方式。为了贴近顾客真实的光顾行为,本文提出了一种考虑顾客便利半径和质量阈值的顾客选择规则,并研究了在该规则下市场中新进入公司的竞争设施选址问题。提出了一种基于排名的遗传算法(RGA)求解该问题,并将该算法与经典遗传算法(GA)和基于排名的离散优化算法(RDOA)进行了比较,结果说明了算法的有效性以及模型中质量阈值的重要性。     

On the Pareto efficiency of term structure targeting policies

In a stochastic economy, monetary policies that rebalance a central bank’s portfolio of short and long term government debt (term structure targeting) can have real effects. When the number of assets equals the number of states of uncertainty, however, this paper shows that the equilibrium allocation is Pareto efficient. Further, all policies with the same short-term interest rate targets support the same equilibrium allocation.     

Controlled Deployment of a Tethered Satellite System

The deployment of a tethered satellite system undoubtedly represents one of the most critical phases in a tether mission: due to its complicated dynamics, high amplitude oscillations are likely to rise in the system, and it will take a long time to reach the desired stable radial equilibrium state. Based on a viscoelastic space billiard model, a targeting strategy is developed in this paper, which makes use of the system's chaotic nature and allows to steer the system into its equilibrium faster and more efficiently compared to conventional strategies.     

Spectral stability results for higher-order operators under perturbations of the domain

We analyze the spectral behavior of higher-order elliptic operators when the domain is perturbed. We provide general spectral stability results for Dirichlet and Neumann boundary conditions. Moreover, we study the bi-harmonic operator with the so-called intermediate boundary conditions. We give special attention to this last case and analyze its behavior when the boundary of the domain has some oscillatory behavior. We will show that there is a critical oscillatory behavior and that the limit problem depends on whether we are above, below or just sitting on this critical value.     

Inducing cooperation by reciprocative strategy in non-zero-sum games

In this paper, we investigate the use of reciprocative strategy to induce cooperative behavior in non-zero-sum games. Reciprocative behavior is defined mathematically in the context of a two-person non-zero-sum game in which both the players have a common set of pure strategies. Conditions under which mutual cooperative behavior results when one of the players responds optimally to reciprocative behavior by the other player are described. Also, the desirability of playing the reciprocative strategy is investigated by stating conditions under which reciprocative strategy by one of the players or by both the players leading to mutual cooperative behavior is a Nash equilibrium outcome.     

Behavior settings and eco-behavioral science: a new arena for mathematical social science permitting a richer and more coherent view of human activities in social systems,part II: Relationships to established disciplines,and needs for mathematical development

Part I of this paper presented the basic concepts of behavior settings and eco-behavioral science originated by the psychologist Roger Barker, showed how they could be linked with standard economic data systems, and suggested their use as a basis for time-allocation matrices and social system accounts. Part II discusses the relationships of behavior settings and eco-behavioral science to established disciplines, describes applications of mathematics to the new concepts by Fox and associates, and points out some major areas in need of mathematical and theoretical development. These areas include representation and measurement of patterns of relationships among roles within behavior settings, relationships among behavior settings within communities and organizations, and the evolution of large, heterogeneous populations of behavior settings over time. We hope some readers will be motivated to participate in this new scientific enterprise.     

BL-general fuzzy automata and accept behavior

In this note, we focus on behavior of BL-general fuzzy automata (for simplicity BL-GFA) and we obtain the free realization for a given behavior, that is, a BL-general fuzzy automaton whose behavior is given behavior. Then we find the realization with the minimum number of states. The minimization takes two steps: at first discard all superfluous states, and then we merge all pairs of states which have the same behavior. Moreover we prove some theorems. In particular, we show that the minimal reduction of the reachable part of an BL-GFA is the minimal realization of the behavior it. Finally we give some examples to clarify these notions.     

Enclosing the behavior of a hybrid automaton up to and beyond a Zeno point

Even simple hybrid automata like the classic bouncing ball can exhibit Zeno behavior. The existence of this type of behavior has so far forced a large class of simulators to either ignore some events or risk looping indefinitely. This in turn forces modelers to either insert ad-hoc restrictions to circumvent Zeno behavior or to abandon hybrid automata. To address this problem, we take a fresh look at event detection and localization. A key insight that emerges from this investigation is that an enclosure for a given time interval can be valid independent of the occurrence of a given event. Such an event can then even occur an unbounded number of times. This insight makes it possible to handle some types of Zeno behavior. If the post-Zeno state is defined explicitly in the given model of the hybrid automaton, the computed enclosure covers the corresponding trajectory that starts from the Zeno point through a restarted evolution.     

Asymptotic Periodicity of Primes Associated to Multigraded Modules

In this paper, we investigate the asymptotic behavior of the set of primes associated to a graded ring extension of Noetherian multigraded rings and modules, and prove that the periodicity occurs in a cone. We also prove the same asymptotic behavior of the grade. The previous known results on this subject are recovered as a special case.