Comparing conventional and distributed approaches to simulation in a complex supply-chain health system

Decision making in modern supply chains can be extremely daunting due to their complex nature. Discrete-event simulation is a technique that can support decision making by providing what-if analysis and evaluation of quantitative data. However, modelling supply chain systems can result in massively large and complicated models that can take a very long time to run even with today's powerful desktop computers. Distributed simulation has been suggested as a possible solution to this problem, by enabling the use of multiple computers to run models. To investigate this claim, this paper presents experiences in implementing a simulation model with a ‘conventional’ approach and with a distributed approach. This study takes place in a healthcare setting, the supply chain of blood from donor to recipient. The study compares conventional and distributed model execution times of a supply chain model simulated in the simulation package Simul8. The results show that the execution time of the conventional approach increases almost linearly with the size of the system and also the simulation run period. However, the distributed approach to this problem follows a more linear distribution of the execution time in terms of system size and run time and appears to offer a practical alternative. On the basis of this, the paper concludes that distributed simulation can be successfully applied in certain situations.     

On the computational behavior of a polynomial-time network flow algorithm

A variation on the Edmonds-Karp scaling approach to the minimum cost network flow problem is examined. This algorithm, which scales costs rather than right-hand sides, also runs in polynomial time. Large-scale computational experiments indicate that the computational behavior of such scaling algorithms may be much better than had been presumed. Within several distributions of square, dense, capacitated transportation problems, a cost scaling code, SCALE, exhibits linear growth in average execution time with the number of edges, while two network simplex codes, RNET and GNET, exhibit greater than linear growth.Our experiments reveal that median and mean execution times are predictable with surprising accuracy for all of the three codes and all three distributions from which test problems were generated. Moreover, for fixed problem size, individual execution times appear to behave as though they are approximately lognormally distributed with constant variance. The experiments also reveal sensitivity of the parameters in the models, and in the models themselves, to variations in the distribution of problems. This argues for caution in the interpretation of such computational studies beyond the realm in which the computations were performed.This work has been supported in part by NSF grants ENG-7910807, ECS-8313853, DMS-8706133, and DDM-8813054, and by AFOSR, NSF, and ONR under NSF grant DMS-8920550 to Cornell University, and by a Sloan Foundation research fellowship held by the first author.     

Stochastic Stability of Some Mechanical Systems

We discuss the behavior, for large values of time, of two linear stochastic mechanical systems. The systems are similar mathematically in that they contain a white noise in their parameters. The initial data may be random as well but are independent of white noise. The expected energy is calculated in both cases. It is well known that for free nonstochastic mechanical systems with viscous damping, the energy approaches zero as time increases. We check that this behavior takes place for the stochastic systems under consideration in the case when the initial data are random but the parameters are not. When the parameters contain a random noise the expected energy may be infinite, approach zero, remain bounded, or increase with no bound. This regime is similar to but more interesting than the known regime for the solutions of differential equations with time dependent periodic coefficients that describes the behavior of a mechanical system with characteristics that are periodic functions of time. We give necessary and sufficient conditions for stability of both systems in terms of the structure of the set of roots of an auxiliary equation.     

一类索赔相关且带干扰的风险模型

该文讨论了索赔时间间隔与索赔量相关且带干扰的风险模型. 借助拉普拉斯变换研究了此模型的破产时刻、破产前瞬间盈余及破产时赤字三者的联合分布,得到了此联合分布拉普拉斯变换的一个分析表达式并讨论了当初始盈余值趋于无穷大时,此联合分布的渐近表达式.     

Experimental study of scheduling with memory constraints using hybrid methods

In this paper we study divisible load scheduling in systems with limited memory. Divisible loads are parallel computations which can be divided into independent parts processed in parallel on remote computers, and the part sizes may be arbitrary. The distributed system is a heterogeneous single level tree. The total size of processor memories is too small to accommodate the whole load at any moment of time. Therefore, the load is distributed in many rounds. Memory reservations have block nature. The problem consists in distributing the load taking into account communication time, computation time, and limited memory buffers so that the whole processing finishes as early as possible. This problem is both combinatorial and algebraic in nature. Therefore, hybrid algorithms are given to solve it. Two algorithms are proposed to solve the combinatorial component. A branch-and-bound algorithm is nearly unusable due to its complexity. Then, a genetic algorithm is proposed with more tractable execution times. For a given solution of the combinatorial part we formulate the solution of the algebraic part as a linear programming problem. An extensive computational study is performed to analyze the impact of various system parameters on the quality of the solutions. From this we were able to infer on the nature of the scheduling problem.     

Parametric modeling of protein–DNA binding kinetics: A discrete event based simulation approach

To understand the stochastic behavior of biological systems, we adopt an “in silico” stochastic event based simulation methodology that can determine the temporal dynamics of different molecules. The main requirement for this technique is the event execution time models for the different biological functions of the system. This paper presents a parametric model to determine the execution time of one such biological function: protein–DNA binding. This biological function is modeled as a combination of microlevel biological events using a coarse-grained probability measure to estimate the stochastic parameters of the function. Our model considers the actual binding mechanism along with some approximated protein and DNA structural information. We use a collision theory based approach to transform the thermal and concentration gradients of this biological function into their corresponding probability measure. This information theoretic approach significantly removes the complexity of the classical protein sliding along the DNA model, improves the speed of computation and can bypass the speed-stability paradox. This model can produce acceptable estimates of DNA–protein binding time necessary for our event based stochastic system simulator where the higher order (more than second order statistics) uncertainties can be ignored. The results show good correspondence with available experimental estimates. The model depends very little on experimentally generated rate constants and brings the important biological parameters and functions into consideration. We also present some “in silico” results showing the effects of protein–DNA binding on gene expression in prokaryotic cells.     

Project Scheduling under Time Dependent Costs – A Branch and Bound Algorithm

In a given project network, execution of each activity in normal duration requires utilization of certain resources. If faster execution of an activity is desired then additional resources at extra cost would be required. Given a project network, the cost structure for each activity and a planning horizon, the project compression problem is concerned with the determination of optimal schedule (duration) of performing each activity while satisfying given restrictions and minimizing the total cost of project execution. This paper considers the project compression problem with time dependent cost structure for each activity. The planning horizon is divided into several regular time intervals over which the cost structure of an activity may vary. But the cost structure of the activities remains the same (constant) within a time interval. Key events of the project attract penalty for finishing earlier or later than the corresponding target times. The objective is to find an optimal project schedule minimizing the total project cost. We present a mathematical model for this problem, develop some heuristics and an exact branch and bound algorithm. Using simulated problems we provide an insight into the computational performances of heuristics and the branch and bound algorithm.     

Experimental and numerical study of the relaxation behavior of facial soft tissue

Challenges in computational simulation of the mechanical behavior of soft tissues and organs for clinical applications are related to the reliability of the models with respect to the anatomy, the mechanical interactions between different tissues, and the non linear (time dependent) force deformation characteristics of soft biological materials. In this paper a 3D finite element model of the face and neck, which has applications in surgical devices optimization and surgery planning, is presented. Bones, muscles, skin, fat, and superficial muscoloaponeurotic system (SMAS) were reconstructed from magnetic resonance images and their shape, constraints and interactions have been modeled according to anatomical, plastic and reconstructive surgery literature. Non linear time dependent constitutive equations are implemented in the numerical model, based on the Rubin-Bodner model. For the present calculations a simplified hyperelastic formulation has been used. The corresponding model parameters were selected according to previous work with mechanical measurements ex vivo on facial soft tissue. For determination of model parameters, in particular the ones corresponding to the time dependent behavior, an instrument for measuring the relaxation behavior of the face tissue in vivo was developed. The experimental set-up is described and results are presented for tests performed on different locations of the face (jaw, mid-face, parotid regions) and neck. The measured “long term” reaction force of the facial soft tissue is compared to numerical results. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Propagation dynamics of a time periodic diffusion equation with degenerate nonlinearity

This paper is on study of traveling wave solutions and asymptotic spreading of a class of time periodic diffusion equations with degenerate nonlinearity. The asymptotic behavior of traveling wave solutions is investigated by using auxiliary equations and a limit process. In addition, the monotonicity and uniqueness, up to translation, of traveling wave solution with critical speed are determined by sliding method. Finally, combining super and sub-solutions and the stability of steady states, some sufficient conditions on asymptotic spreading are given, which indicates that the success or failure of asymptotic spreading are dependent on the degeneracy of nonlinearity as well as the size of compact support of initial value.     

Monitoring of dynamic processes by rectangular hybrid automata

In this paper we develop a method of monitoring dynamic processes based on rectangular hybrid automats. This method takes into account the behavior of the system and the evolution of its parameters. A failure during the execution of the process can lead to a dysfunctional state in the system.The monitoring system, we propose, makes it possible to detect this state of dysfunction as soon as possible thanks to the reachability analysis.     

Minimizing the response time of executing a join between fragmented relations in a distributed database system

The problem of describing minimal response time execution strategies in evaluating the join of several fragmented database relations, is considered. The consequential optimization problem assumes the convenient form of a min-max integer program. With further attention, various generalizations are realized that also include the performance objective of total execution cost.Tables of data logically conforming to the relational model of information are, at the physical level, frequently divided into numerous pieces. These fragments are found disseminated amongst the various sites of a distributed database system, with each one possibly replicated at any number of separate facilities.A submission demanding the amalgamation of many such relations is resolved by joining together their sets of component fragments in an appropriate manner, as defined by complicated patterns of overlapping attribute values. The final result is realized by then concatenating the products of these computations. This process is to be performed under the supervision of the database management system in such a way as to minimize the time taken, as perceived by the user who issued the request.These developments are based upon earlier investigations [1–5] that consider only the alternative optimization goal of minimal execution cost. With this in mind, several different different approaches may be taken to realize distinct hybrid models that give due regard to both measures of join query performance.     

Efficiency and production rate of a transfer line with two machines and a finite storage buffer

A markov model for a transfer line with two unreliable machines separated by a finite storage size buffer is introduced. Service time distribution for the two machines is Erlang whereas failure and repair times are assumed to be exponential random variables. The paper presents an efficient method to solve analytically the steady state probabilities of the system. This method is independent of the buffer size. We also include in the paper a study of the behavior of some systems performance measures such as the efficiency of the two machines and the production rate of the system.     

Tiling optimization for the solution of two-dimensional time-dependent heat equation

Tiling optimization for the solution of the Dirichlet problem for the two-dimensional heat equation on computers with distributed memory is investigated. Estimates of the amount of communications and computations are obtained. The tiling optimization problem is reduced to the minimization of a function that explicitly expresses the dependence of the execution time on the tile size and the parameters of the target supercomputer—the dimension and size of the computing environment, processor performance, initialization time, and capacity of the communication channels.     

机构投资者的最优变现策略

在投资、变现等大宗交易过程中,资产交易价格与交易策略密切相关,因此,交易的完成过程需要很高的技巧.文章讨论了机构投资者的最优变现策略问题,假设证券价格服从几何布朗运动,以均值方差效用为目标函数,得到了最优变现策略所满足的二阶微分方程,并由差分法得到其数值解.最后,由参数的敏感性分析知:最优变现策略与瞬时冲击、市场波动率及风险厌恶系数等参数有关,但与永久冲击无关,且最优变现策略对市场波动率和瞬时冲击的变化较敏感.     

Computation of the steady state distribution for multi-server retrial queues with phase type service process

We consider a multi-server retrial queueing system with the Batch Markovian Arrival Process and phase type service time distribution. Such a general queueing system suits for modeling and decision making in many real life objects including modern wireless communication networks. Behavior of such a system is described by the level dependent multi-dimensional Markov chain. Blocks of the generator of this chain, which is the block structured matrix of infinite size, can have large size if the number of servers is large and distribution of service time is not exponential. Due to this fact, the existing in literature algorithms allow to compute key performance measures of such a system only for a small number of servers. Here we describe the algorithm that allows to compute the stationary distribution of the system for larger number of servers and numerically illustrate its advantage. Importance of taking into account correlation in the arrival process is numerically demonstrated.     

Chameleon based on clustering feature tree and its application in customer segmentation

Clustering analysis plays an important role in the filed of data mining. Nowadays, hierarchical clustering technique is becoming one of the most widely used clustering techniques. However, for most algorithms of hierarchical clustering technique, the requirements of high execution efficiency and high accuracy of clustering result cannot be met at the same time. After analyzing the advantages and disadvantages of the hierarchical algorithms, the paper puts forward a two-stage clustering algorithm, named Chameleon Based on Clustering Feature Tree (CBCFT), which hybridizes the Clustering Tree of algorithm BIRCH with algorithm CHAMELEON. By calculating the time complexity of CBCFT, the paper argues that the time complexity of CBCFT increases linearly with the number of data. By experimenting on sample data set, this paper demonstrates that CBCFT is able to identify clusters with large variance in size and shape and is robust to outliers. Moreover, the result of CBCFT is as similar as that of CHAMELEON, but CBCFT overcomes the shortcoming of the low execution efficiency of CHAMELEON. Although the execution time of CBCFT is longer than BIRCH, the clustering result of CBCFT is much satisfactory than that of BIRCH. Finally, through a case of customer segmentation of Chinese Petroleum Corp. HUBEI branch; the paper demonstrates that the clustering result of the case is meaningful and useful. The research is partially supported by National Natural Science Foundation of China (grants #70372049 and #70121001).     

Busy period analysis of the level dependent PH/PH/1/K queue

In this paper, we study the transient behavior of a level dependent single server queuing system with a waiting room of finite size during the busy period. The focus is on the level dependent PH/PH/1/K queue. We derive in closed form the joint transform of the length of the busy period, the number of customers served during the busy period, and the number of losses during the busy period. We differentiate between two types of losses: the overflow losses that are due to a full queue and the losses due to an admission controller. For the M/PH/1/K, M/PH/1/K under a threshold policy, and PH/M/1/K queues, we determine simple expressions for their joint transforms.     

An efficient parallel method for batched OS-ELM training using MapReduce

In this era of big data, more and more models need to be trained to mine useful knowledge from large scale data. It has become a challenging problem to train multiple models accurately and efficiently so as to make full use of limited computing resources. As one of ELM variants, online sequential extreme learning machine (OS-ELM) provides a method to learn from incremental data. MapReduce, which provides a simple, scalable and fault-tolerant framework, can be utilized for large scale learning. In this paper, we propose an efficient parallel method for batched online sequential extreme learning machine (BPOS-ELM) training using MapReduce. Map execution time is estimated with historical statistics, where regression method and inverse distance weighted interpolation method are used. Reduce execution time is estimated based on complexity analysis and regression method. Based on the estimations, BPOS-ELM generates a Map execution plan and a Reduce execution plan. Finally, BPOS-ELM launches one MapReduce job to train multiple OS-ELM models according to the generated execution plan, and collects execution information to further improve estimation accuracy. Our proposal is evaluated with real and synthetic data. The experimental results show that the accuracy of BPOS-ELM is at the same level as those of OS-ELM and parallel OS-ELM (POS-ELM) with higher training efficiencies.     

Semi-Resonant Interactions and Frequency Dividers

A theory describing the behavior of a system as it evolves slowly through internal nonlinear resonances is presented. The energy sharing process is seen to be quite complex as it depends crucially on both nonlinear and frequency detuning effects. Two phenomena are discussed in detail although the general ideas are applicable to many situations. Firstly we examine the interaction between the quadratically coupled oscillators whose natural frequencies are in the ratio 2:1 for a limited period of time. Such a system is shown to be an extremely useful switching device. Secondly we examine the time dependent Duffing equation and find that smooth forward and reverse transitions occur without the presence of dissipation.     

时延混成系统的切换控制器合成

如何设计安全、可靠的信息物理融合系统是计算机科学和控制理论面临的一个重大挑战.时延现象在信息物理融合系统中普遍存在,时延对系统的稳定性、安全性和控制性能具有实质性影响.但是在已有时延系统验证和控制器合成的工作中往往忽略时延因素,这会导致在不考虑时延情况下能保证稳定和安全的系统在实际运行时因为时延原因而不再稳定和安全.因为时延使得系统的行为演化不仅与当前状态有关,还依赖于系统的历史状态,所以时延混成系统的验证和控制合成更加困难.本文研究信息物理融合系统在考虑时延情形下切换控制器合成问题,提出基于不变式生成技术的控制器合成方法.首先,利用谱分析和线性化技术将时延系统的微分不变式生成问题归结为有界时间的可达集计算问题;然后,提出基于抽象精化的算法计算时延系统有界时间可达集的上近似;最后,实现本文算法并使用实例验证该方法的有效性.