大额资产清仓的自动化交易策略

市场的机构投资者经常需要清仓手中持有的大额资产, 因此清仓的交易策略成为了关心的问题. 以工商银行的股票为例,给出适用于计算机执行的自动化清仓策略. 首先将高频的工商银行股票历史数据在每个交易日分别划分出48个交易期, 将问题简化为处理每个交易日交易期的数据. 在此基础上, 综合考虑用神经网络模拟预测清仓时股票价格随时间下降的风险和用信息流理论模型衡量的价格冲击和交易时刻, 并通过优化模型得到清仓持续的交易日天数. 此后, 再制定出每个交易日的具体自动化交易策略.在制定日内交易策略 时, 首先用神经网络对交易时刻做出预测, 然后综合考虑使用 VWAP 预测出的交易量和通过 Kalman 滤波方法修正过的期权定价公式预测出的各时刻股票的初始价格, 最终给出详细的交易策略及交易的成本.     

Modeling and analysis of machine sharing in manufacturing systems

The issue of machine sharing arises quite frequently in the design and operation of automated manufacturing systems. It is often championed as a mechanism for enhancing the flexibility and versatility of these systems. However despite its importance, our understanding of machine sharing and of its effect on system performance has remained inadequate, relying mainly on anecdotal data or limited empirical evidence. In this paper, we present an analytical model that captures the various dimensions of machine sharing and use this model to study the effect of machine sharing on performance of manufacturing systems. In particular, we examine the relationship between machine sharing and several performance measures, such as production rate, machine utilization, flow time and work-in-process inventory, for varying assumptions of system utilization, setup times, batch sizes and demand and processing variability. These relationships are then used to identify conditions under which machine sharing is of value and to determine the corresponding optimal sharing levels.     

Regenerative pull (Kanban) production control policies

A production system consists of a set of parallel robotic cells manufacturing parts for several distinct work stations. The stations order parts from these cells and withdraw parts from their buffers only at the rate and at the time of consumption. The desired decision vector provides for the instantaneous number of cells assigned to produce parts for each work station. Two novel tractable and optimal regenerative pull (‘Kanban’) control policies are formulated: one policy minimizes the weighted starvation penalty, while the other maximizes the weighted throughputs per unit time. Following these regenerative policies the production schedules are re-evaluated at each decision epoch to mitigate the effects of processing time variability.Several important properties regarding the inherent interaction between the structure of the optimal policy, the performance of the system and the desired allocation of productive capabilities among the manufacturing resources are examplified. It is shown that the optimal policy attempts to marginally assign as much of the cells capacity as possible to certain critical part types. Substantial changes in the structure of the optimal policy, resulting either from incrementing the number of cells or from increasing their capacity, are also identified. More generally, attention is drawn to the qualitative behavior of the optimal pull control policy in certain manufacturing systems with stochastic processing rates.     

Some Problems Associated with the Distribution of Consumer Products

The distribution problem is considered as a whole. The interconnexions are shown between various subproblems: factory siting, warehouse (or depot) siting, subdepot siting, allocation of production resources to factory sites and minimization of costs. It is suggested that the results obtained for certain products distributed nationally through grocery outlets are valid (with qualifications) for any nationally marketed consumer product. The use of traditional operational research techniques, where appropriate, is referred to but not in great detail. A logical approach to siting problems, particularly the siting of a large number of subdepots, is outlined. The aim of this approach is to obtain the correct answers with the minimum amount of work. The implications for marketing are discussed with particular reference to costs: the cost of distributing goods to certain areas may be unduly high; the cost of customer service may rise disproportionately as the level of service given rises. A balance must be struck which is in line with the company's aims but which may mean modifying production, distribution and sales objectives.     

Decision architectures for production planning in multi-stage multi-product manufacturing systems

Recent trends in automated manufacturing call for hierarchical decision architectures for production planning, suitable for integration with part flow controls. Different design approaches are currently adopted for implementing production planning architectures, depending either on the objective of defining a centralized production plan for the whole manufacturing system (as in the case of MRP and OPT), or on the desire of coordinating local plans for the component work cells (as for JIT). The paper analyzes such approaches by use of a unifying mathematical formulation of the production plan optimization problem, to recognize the main features of the existing planning approaches, and compare their usefulness in different manufacturing processes.     

Distributing decision making using Java simulation across the World Wide Web

This paper describes a prototype distributed, multi-user Internet based simulation environment, written in Java, and its application to decision making. An example of its use is presented in the context of manufacturing. The motivating factor behind this work is the rapid development in computer controlled plants and systems, such as automated production lines. The growth in flexibility offered by computer control has led to increasing speed and complexity in scheduling of these systems. Making such decisions often requires the very high costs of moving expert modellers and Operational Research staff to factory sites. Following developments in computer supported concurrent working (CSCW) and concurrent engineering, it is suggested that a means for working in a geographically distributed manner is desirable. The availability of Internet based solutions, exploiting Java's distributed client server architecture makes it possible to prototype such ideas in a generally accessible manner. An environment built along those lines is described here. Its benefits are shown through a case study and ideas for future work are explored.     

Limit-cycle-like control for 2-dimensional discrete-time nonlinear control systems and its application to the Hénon map

In this paper, a control method that generates a desired limit-cycle-like behavior for a 2-dimensional discrete-time nonlinear control system is discussed. First, we define some notations and state the problem formulation. Next, a necessary and sufficient condition of existence of a control input that realizes a desired limit-cycle-like behavior is shown. We then derive a control algorithm to solve the problem on generating limit-cycle-like behaviors, and a modification of the algorithm is also shown. Finally, we apply the two types of algorithms to a chaotic system, the Hénon map, in order to indicate the availability of the proposed method. In addition, by using the control method, we also consider a stabilization problem for the Hénon map.     

Two-dimensional heat and mass transfer during drying of deformable media

Drying is an essential step in many production and treatment processes. The control of the dry product quality is more and more required in order to ensure effective use or handling of the material. The aim of this study is to develop a two-dimensional drying model which takes into account heat and mass transfer and the accompanying deformation of the dried material. The model tries to be relatively simple but sufficiently complete in order to predict and analyze the spatio-temporal distribution of the temperature, the moisture and the solid displacement during the process. The product was considered as a two-phases, homogeneous, hygroscopic, isotropic and highly shrinkable medium. The model was solved numerically by a finite difference method. The simulation allowed the obtention of the time and space evolutions of several parameters such as product temperature, moisture content and solid displacement.     

Asymptotic behavior of spectral of Neumann‐Poincaré operator in Helmholtz system

In this paper, we are concerned with the asymptotic behavior of the Neumann‐Poincaré operator in Helmholtz system. By analyzing the asymptotic behavior of spherical Bessel function near the origin and/or approach higher order, we prove the asymptotic behavior of spectral of Neumann‐Poincaré operator when frequency is small enough and/or the order is large enough. The results show that spectral of Neumann‐Poincaré operator is continuous at the origin and converges to 0 from the complex plane in general.     

集团分布式制造模式下生产调配优化模型研究及算法设计

基于分布式概念的集团分布式制造生产管理模式在市场中占据着越来越重要的地位,此种运营模式由制造型企业向服务型企业蔓延的趋势也越来越明显,然而针对这一具有自身特点的集团分布式概念下的生产管理模型的调度研究却很少。研究针对此生产管理模式下集团级的生产调配问题建立数学模型,综合考虑客户订单的分散情况、各分厂日生产能力限制和产品品种多样性的特点,采用改进的遗传算法求解该模型,提出一种基于订单和工厂的两段式非负整数染色体编码方法,保证了生产能力约束和订单约束,采用PMX交叉算法避免不合法染色体的出现。选取W集团一定计划期内的客户订单数据进行实例分析,验证了该生产调配模型和算法的有效性。     

Modal criteria for robust optimization of vibroacoustic systems

This work is an extension of the work done in previous papers (Besset and Jézéquel in Intern J Numer Method Eng 70(5):523–542, 2007; J Vib Acoust 130(1):011008, 2008; Intern J Numer Method Eng 73:1347–1373, 2008; J Vib Acoust 130(3):031009, 2008). It deals with modal criteria allowing to process optimization of structures including robustness. The system considered in the paper is a fluid-structure system. The aim of the paper is to use component mode synthesis methods to optimize the geometry of the structure and the robustness with respect to the design parameter variations of its vibroacoustic behaviour. Two criteria will be proposed. The first one is directly linked to the pressure level in the acoustic cavity. The second one is linked to the robustness of the methods. It comes from the polynomial chaos study of the considered system. A classical multiobjective optimization is then processed and Pareto graphics are proposed to represent the optimal solutions of the optimization problem.     

Internal transport in automated semiconductor manufacturing systems

This paper summarizes the main results presented by the author in his PhD thesis (Montoya-Torres 2005), supervised by Stéphane Dauzèere-Pérés, Jean-Pierre Campagne and Hélène Marian, and defended on 29 November 2005 at the école des Mines de Saint-étienne and Université Jean-Monnet. The thesis is written in French and is available upon request from the author. This work deals with a real-life transportation problem in the semiconductor industry. It proposes a new approach by integrating tactical and operational decisions for the control of the automated transport system. At the tactical level, the problem is modeled using integer linear programming models inspired from Location Theory. At the operational level, the solution obtained from the tactical optimization is coupled with a discrete-event computer simulation program and some policies for transportation operations are implemented and compared.     

A multi-state model to improve the design of an automated system to monitor the activity patterns of patients with bipolar disorder

This paper describes the role of mathematical modelling in the design and evaluation of an automated system of wearable and environmental sensors called PAM (Personalised Ambient Monitoring) to monitor the activity patterns of patients with bipolar disorder (BD). The modelling work was part of an EPSRC-funded project, also involving biomedical engineers and computer scientists, to develop a prototype PAM system. BD is a chronic, disabling mental illness associated with recurrent severe episodes of mania and depression, interspersed with periods of remission. Early detection of the onset of an acute episode is crucial for effective treatment and control. The aim of PAM is to enable patients with BD to self-manage their condition, by identifying the person's normal ‘activity signature’ and thus automatically detecting tiny changes in behaviour patterns which could herald the possible onset of an acute episode. PAM then alerts the patient to take appropriate action in time to prevent further deterioration and possible hospitalisation. A disease state transition model for BD was developed, using data from the clinical literature, and then used stochastically in a Monte Carlo simulation to test a wide range of monitoring scenarios. The minimum best set of sensors suitable to detect the onset of acute episodes (of both mania and depression) is identified, and the performance of the PAM system evaluated for a range of personalised choices of sensors.     

Fluid queues with synchronized output

We present a model of parallel Lévy-driven queues that mix their output into a final product; whatever cannot be mixed is sold on the open market for a lower price. The queues incur holding and capacity costs and can choose their processing rates. We solve the ensuing centralized (system optimal) and decentralized (individual station optimal) profit optimization problems. In equilibrium the queues process work faster than desirable from a system point of view. Several model extensions are also discussed.     

A queueing model of delayed product differentiation

We consider a production system in which a supplier produces semi-finished items on a make-to-stock basis for a manufacturer that will customize the items on a make-to-order basis. The proportion of total processing time undertaken by the supplier determines how suitable the semi-finished items will be to meet customer demand. The manufacturer wishes to determine the optimal point of differentiation (the proportion of processing completed by the supplier) and its optimal semi-finished goods buffer size. We use matrix geometric methods to evaluate various performance measures for this system, and then, with enumeration techniques, obtain optimal solutions. We find that delayed product differentiation is attractive when the manufacturer can balance the costs of customer order fulfillment delay with the costs associated with unsuitable items.     

Dynamic interactive stabilization of the switching Kumar-Seidman system

A dynamic control protocol for the Kumar-Seidman flexible production system represented in general algebraic form is suggested. The ultimate purpose of the study is to minimize the total amount of work per unit time. The suggested protocol is proved to generate the required periodic process as a global attractor. In order to substantiate convergence, a number of statements of classical Frobenius-Perron theory are generalized to monotone piecewise affine nonlinear operators. A new method for exciting the required production cycles in the spirit of classical Poincaré’s method is suggested. The approach is based on a new stability criterion for an equilibrium of a discrete stationary system. A dynamic control protocol for the Kumar-Seidman flexible production system represented in general algebraic form is suggested and proved to generate the required periodic process as a global attractor. In order to substantiate convergence, a number of statements of classical Frobenius-Perron theory are generalized to monotone piecewise affine nonlinear operators.     

Compaction and Consolidation of Aramid and Composite Fibers. 2. Consolidation of Composite Fibers

The transverse compaction and consolidation of composite fibers obtained from blends of rigid-chain aromatic polyamides and a thermoplastic polycaproamide PA-6 are investigated with the aim to predict the fiber behavior during their compression and processing into plastics. Introduction of the aliphatic polyamide PA-6 into aramid fibers considerably increases their transverse compliance and promotes their sintering. A method for calculating the viscosity of the thermoplastic in the interfiber space from the ratio between the volumetric rate of compaction and the porosity of the material is proposed. It is found that the effective viscosity of the PA-6 melt, during its flow in the thin interfibrillar layers under compression, grows with decrease in its content in the composite fibers.     

Detecting tail behavior: mean excess plots with confidence bounds

In many practical situations exploratory plots are helpful in understanding tail behavior of sample data. The Mean Excess plot is one of the exploratory tools often used in practice to understand the right tail behavior of a data set. It is known that if the underlying distribution of a data sample is in the maximum domain of attraction of a Fréchet, a Gumbel or a Weibull distributions then the ME plot of the data approaches a straight line in an appropriate sense, with positive, zero or negative slope respectively. In this paper we construct confidence intervals around the ME plots which assist us in ascertaining which particular maximum domain of attraction the data set comes from. We recall weak limit results for the Fréchet domain of attraction, already obtained in Das and Ghosh (Bernoulli 19, 308–342 2013) and derive weak limits for the Gumbel and Weibull domains in order to construct confidence bounds. We demonstrate our methodology by applying them to simulated and real data sets.     

Modelling and scheduling of an asynchronous cyclic production line with multiple parts

In this study, we model and analyse a production line with asynchronous part transfers, processing time variability, and cyclic scheduling in the same framework. We consider a production line with multiple parts and finite interstation buffers. The line produces a batch of n jobs repetitively using the same order of jobs in every batch. The processing time of a job on a station is a random variable and is assumed to have a phase-type distribution. Parts are transferred between the stations in an asynchronous manner. We first present a continuous time Markov chain model to analyse the performance of this system for a given sequence. A state-space representation of the model and the associated rate matrix are generated automatically. The steady state probabilities of the Markov chain are determined by using a recursive method that exploits the special structure of the rate matrix. The cycle time, the production rate, and the expected Work-In-Progress (WIP) inventory are used as the main performance measures. We then present an approximate procedure to determine the cyclic sequence that minimises the cycle time. We then investigate the effects of operating decisions, system structure, processing time variability, and their interaction in the same framework. Numerical results for the performance evaluation and scheduling of cyclic production lines are also presented.     

Discovering the dynamic behavior of unknown systems using fuzzy logic

To know the dynamic behavior of a system it is convenient to have a good dynamic model of it. However, in many cases it is not possible either because of its complexity or because of the lack of knowledge of the laws involved in its operation. In these cases, obtaining models from input–output data is shown as a highly effective technique. Specifically, intelligent modeling techniques have become important in recent years in this field. Among these techniques, fuzzy logic is especially interesting because it allows to incorporate to the model the knowledge that is possessed of the system, besides offering a more interpretable model than other techniques. A fuzzy model is, formally speaking, a mathematical model. Therefore, this model can be used to analyze the original system using known systems analysis techniques. In this paper a methodology for extract information from unknown systems using fuzzy logic is presented. More precisely, it is presented the exact linearization of a Takagi–Sugeno fuzzy model with no restrictions in use or distribution of its membership functions, as well as obtaining its equilibrium states, the study of its local behavior and the search for periodic orbits by the application of Poincaré.