VRPTW的扰动恢复及其TABU SEARCH算法

本文对带时间窗的车辆路线安排扰动恢复问题进行了讨论,分析了各种可能的扰动:增加减少客户,时间窗、客户需求及路线可行性的扰动,构造了扰动模型.利用禁忌搜索算法对问题进行求解,同时通过对模型参数重新设置,得到了多个满足要求的不同的解,这样使解更具有实际可行性和有效性.     

Carathéodory's method for a class of dynamic games

The method of equivalent variational methods, originally due to Carathéodory for free problems in the calculus of variations is extended to investigate feedback Nash equilibria for a class of n-person differential games. Both the finite-horizon and infinite-horizon cases are considered. Examples are given to illustrate the presented results.     

An optical measurement of vortex shape at a free surface

We have proposed an optical method of vortex shape measurement based on Fourier transform profilometry (FTP) and verified it by experiment. The results of our experiment proposed in this paper show that FTP can efficiently reconstruct the vortex shape at a free surface and this method is suitable for wide use in studying such problems as liquid shear flow, wake of an object, flow behind a bluff body, and wetting angle.     

On effectiveness of wiretap programs in mapping social networks

Snowball sampling methods are known to be a biased toward highly connected actors and consequently produce core-periphery networks when these may not necessarily be present. This leads to a biased perception of the underlying network which can have negative policy consequences, as in the identification of terrorist networks. When snowball sampling is used, the potential overload of the information collection system is a distinct problem due to the exponential growth of the number of suspects to be monitored. In this paper, we focus on evaluating the effectiveness of a wiretapping program in terms of its ability to map the rapidly evolving networks within a covert organization. By running a series of simulation-based experiments, we are able to evaluate a broad spectrum of information gathering regimes based on a consistent set of criteria. We conclude by proposing a set of information gathering programs that achieve higher effectiveness then snowball sampling, and at a lower cost. Maksim Tsvetovat is an Assistant Professor at the Center for Social Complexity and department of Public and International Affairs at George Mason University, Fairfax, VA. He received his Ph.D. from the Computation, Organizations and Society program in the School of Computer Science, Carnegie Mellon University. His dissertation was centered on use of artificial intelligence techniques such as planning and semantic reasoning as a means of studying behavior and evolution of complex social networks, such as these of terrorist organizations. He received a Master of Science degree from University of Minnesota with a specialization in Artificial Intelligence and design of Multi-Agent Systems, and has also extensively studied organization theory and social science research methods. His research is centered on building high-fidelity simulations of social and organizational systems using concepts from distributed artificial intelligence and multi-agent systems. Other projects focus on social network analysis for mapping of internal corporate networks or study of covert and terrorist orgnaizations. Maksim’s vita and publications can be found on Kathleen M. Carley is a professor in the School of Computer Science at Carnegie Mellon University and the director of the center for Compuational Analysis of Social and Organizational Systems (CASOS) which has over 25 members, both students and research staff. Her research combines cognitive science, social networks and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion and response within and among groups particularly in disaster or crisis situations. She and her lab have developed infrastructure tools for analyzing large scale dynamic networks and various multi-agent simulation systems. The infrastructure tools include ORA, a statistical toolkit for analyzing and visualizing multi-dimensional networks. ORA results are organized into reports that meet various needs such as the management report, the mental model report, and the intelligence report. Another tool is AutoMap, a text-mining systems for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource and task networks. Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed in the counter-terrorism area are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills, and weaponized biological attacks; DyNet a model of the change in covert networks, naturally and in response to attacks, under varying levels of information uncertainty; and RTE a model for examining state failure and the escalation of conflict at the city, state, nation, and international as changes occur within and among red, blue, and green forces. She is the founding co-editor with Al. Wallace of the journal Computational Organization Theory and has co-edited several books and written over 100 articles in the computational organizations and dynamic network area. Her publications can be found at: http://www.casos.cs.cmu.edu/bios/carley/publications.php     

基于MATLAB的异步电动机线性化控制系统的仿真

从异步电动机在同步旋转坐标系下的状态方程出发，在一定的条件下，对其系数矩阵简化．推出异步电动机的线性化控制模型．并基于该模型得出异步电动机的线性化控制系统．以给定电机为例，对该模型的有效性、响应用MATLAB进行仿真分析．验证的结果说明上述模型具有实用价值．     

免疫算法在车辆调度问题中的应用

免疫算法是模仿生物体高度进化、复杂的免疫系统仿生的一种智能化启发式算法。本文根据车辆调度问题的具体情况，应用免疫算法解决车辆调度中路线安排问题，并提出了一种基于分组匹配的亲和力的计算方法。实验结果表明，免疫算法能有效地应用于车辆调度中路线安排问题。     

The Sample Average Approximation Method Applied to Stochastic Routing Problems: A Computational Study

The sample average approximation (SAA) method is an approach for solving stochastic optimization problems by using Monte Carlo simulation. In this technique the expected objective function of the stochastic problem is approximated by a sample average estimate derived from a random sample. The resulting sample average approximating problem is then solved by deterministic optimization techniques. The process is repeated with different samples to obtain candidate solutions along with statistical estimates of their optimality gaps.We present a detailed computational study of the application of the SAA method to solve three classes of stochastic routing problems. These stochastic problems involve an extremely large number of scenarios and first-stage integer variables. For each of the three problem classes, we use decomposition and branch-and-cut to solve the approximating problem within the SAA scheme. Our computational results indicate that the proposed method is successful in solving problems with up to 2¹⁶⁹⁴ scenarios to within an estimated 1.0% of optimality. Furthermore, a surprising observation is that the number of optimality cuts required to solve the approximating problem to optimality does not significantly increase with the size of the sample. Therefore, the observed computation times needed to find optimal solutions to the approximating problems grow only linearly with the sample size. As a result, we are able to find provably near-optimal solutions to these difficult stochastic programs using only a moderate amount of computation time.     

Influence of surfactant and lipid chain length on the solubilisation of phosphatidylcholine vesicles by micelles comprised of polyoxyethylene sorbitan monoesters

Photon correlation spectroscopy and freeze-fracture electron microscopy have been used to determine the ability of a range of micelle-forming, polyoxyethylene (20) sorbitan monoesters (Tweens) to solubilise vesicles prepared from phosphatidylcholines of different acyl chain lengths and degrees of saturation with a view to rationalising (in terms of their membrane toxicity) which of the micelle-forming surfactants to use as drug delivery vehicles. The phosphatidylcholines used were dimyristoyl-, dipalmitoyl-, distearoyl- and dioleoylphosphatidylcholine (DMPC, DPPC, DSPC and DOPC, respectively) while the nonionic polyoxyethylene sorbitan monoesters studied were polyoxyethylene (20) sorbitan monolaurate (Tween 20), a 9:1 weight ratio mixture of polyoxyethylene (20) sorbitan monopalmitate and monostearate (Tween 40), a 1:1 weight ratio mixture of polyoxyethylene (20) sorbitan monopalmitate and monostearate (Tween 60), and polyoxyethylene (20) sorbitan monooleate (Tween 80). The ability of the Tween micelles to solubilise phospholipid vesicles was found to depend both upon the length of the surfactant acyl chain and the length of the acyl chains of the phospholipid comprising the vesicle. Vesicles composed of long saturated diacyl chain phospholipids, namely DSPC and DPPC, were the most resistant to solubilisation, while those prepared from the shorter acyl chained DMPC were more readily solubilised. In terms of their solubilisation behaviour, vesicles made from phospholipids containing long, unsaturated acyl chains, namely DOPC behaved more akin to those vesicles prepared from DMPC. None of the Tween surfactants were effective at solubilising vesicles prepared from DPPC or DSPC. In contrast, there were clear differences in the ability of the various surfactants to solubilise vesicles prepared from DMPC and DOPC, in that micelles formed from Tween 20 were the most effective solubilising agent while those formed by Tween 60 were the least effective. As a consequence of these observations it was considered that Tween 60 was the surfactant least likely to cause membrane damage in vivo and, therefore, is the most suitable surfactant for use as a micellar drug delivery vehicle.