A Dynamic Stochastic Model of Asset Pricing with Heterogeneous Beliefs

This paper presents a new stochastic asset pricing model in a context of bounded rationality, where beliefs about future prices are formed via an expectations updating rule characterized by a stochastic multiplicative random variable, working as an agent-based time dependent weight of the conditional expectation of the fundamental. The agent’s belief about future prices depends on his confidence in the forecasts made by other agents, measured by the distribution type of agents and by a confidence parameter. The resulting stochastic dynamical system is firstly analyzed in a deterministic setting, deriving conditions for uniqueness and stability of steady states and proving that, for high values of the confidence parameter, no complicated dynamics can be exhibited, hence the new component has a stabilizing effect on the qualitative dynamics. Differently, for small values of the confidence parameter, we prove the existence of a stability region in the parameters plane where the only possible dynamics is convergence to a steady state, while complexity is exhibited outside such region. Starting from the results obtained in the deterministic case, the model is then explored by reintroducing randomness. More specifically, we analyze the stability region in three directions: first of all, a robust estimate of the stability region’s measure is provided; second, a long run equilibrium relation between the parameters of the system is obtained; third, the persistence properties of the series describing the bifurcation curves is performed. We finally underline some economic implications.     

Dynamic Congestion Pricing in Disequilibrium

A theory of dynamic congestion pricing for the day-to-day time scale is presented which takes the form of a continuous time optimal control problem. The formulation accomodates elastic nonseparable travel demands and nonseparable travel costs. Necessary conditions for optimal congestion prices are analyzed to uncover bang-bang, singular and synthesized optimal control decison rules for setting network tolls in a dynamic environment. These decision rules are shown to be sufficient for optimality under plausible regularity conditions.     

Flexible Labour Strategy in the Dutch Automotive Industry

Labour flexibility is a major way for companies to become more flexible. Why companies use flexible labour relations varies widely per industry. We assess the development of labour flexibility within the Dutch automotive industry. Four cases, together representing the production chain, are presented. We show how and why these companies arrived at the high level of sophistication in labour relations they currently have and what combinations of internal and external, numerical and functional forms have emerged. The process has been one of trial and error, characterised by emerging rather than deliberate strategy. It has a clear pattern over time. In three out of our four companies, an innovative labour use strategy emerged, finely tuned to market demands, new institutional realities and specific company needs.     

Dynamic Pricing on the Internet: Theory and Simulations

As is the case with traditional markets, the sellers on the Internet do not usually know the demand functions of their customers. However, in such a digital environment, a seller can experiment different prices in order to maximize his profits. In this paper, we fit the dynamic pricing model of Rothschild (1974) to match the pricing problem of a Web-store. In this setting, we define the optimization problem of a Web-store and by simulations we study the price dynamics that can appear when all the sellers on a given market follow an optimal pricing policy.     

Unlocking the Advantages of Dynamic Service Selection and Pricing

Bandwidth limitations, resource greedy applications verbose mark-up languages and an increasing number of voice and data users are straining the air interface of wireless networks. Hence, novel approaches and new algorithms to manage wireless bandwidth are needed. In addition, usage based pricing is becoming increasingly prevalent (pre-paid cell phones, calling cards, non-contract minutes, etc.). This paper unlocks the potential to improving the performance of overall system behavior by allowing users to change service level and/or service provider for a (small) price. The ability to dynamically re-negotiate service gives the user the power to control QoS while minimizing usage cost. On the other hand, the ability to change service level pricing dynamically allows the service providers to manage traffic better, improve resource usage and most importantly maximize their profit. This provides a surprising win-win situation for BOTH the service providers AND the users. In this paper we present easy to implement on-line algorithms to minimize the overall usage cost to individual mobile users. This on-line algorithm continuously receives pricing information and evaluates minimum QoS requirements. The algorithm then determines appropriate service level, chooses a service provider and sets a time for re-negotiation dynamically. Our algorithm can handle many practical issues such as capacity limitations, arbitrary price fluctuations and loss/gain of service providers due to mobility. Our results do not assume any specific technologies and can be applied to any environment that can employ dynamic pricing, including wired networks. In fact, dynamic pricing is becoming increasingly desirable since service provider and capacity changes are a growing by-product of mobility. Arriving and departing users at/from a cell tower (or wireless LAN) can effectively reduce or increase the available bandwidth in a cell (or LAN transmission area) and represents a natural opportunity for a pricing change.     

浅谈计算机控制系统及在汽车行业的应用

随着科学技术的发展,计算机的应用已渗透到社会的各行各业,正在改变着传统的工作、学习和生活方式,推动着社会的发展,成为人类生活中必不可少的一部分。本文着重阐述了计算机控制系统的组成、功能及其在汽车行业的应用。     

动态构造虚拟公共网络服务的一个多agent协商模型

该文通过对IP网络管理中多个移动agent动态构造虚拟公共网络VPN的研究,采用基于QoS服务的多属性的动态协商定价模型,在多agent之间形成了利益最大化的服务协议,以此应用实例表明移动agent是解决异构、分布、自治环境的复杂IP网管的有效软件体系结构。     

新技术趋势下汽车工业中的系统仿真技术

综述新技术发展趋势下汽车工业对系统仿真技术的新的需求.新技术趋势主要是汽车新四化:电动化、智能化、网联化、共享化.所涉及到的系统仿真技术主要包括:电动化对系统仿真技术的需求,电动化对整车动力经济性及其它性能带来的改变以及对仿真的需求,电动化关键零部件的仿真需求;智能化对系统仿真技术的需求,整车动力学的发展,引入传感...     

Pricing Model in the Walras Economic Equilibrium Scheme

Useful formulas of pricing in terms of labor costs are obtained in a scheme with n individuals and m products. They are derived from systems of balance equations for supply and demand in the labor, produce, and capital markets, with regard for the types of production and utility functions.     

A Link-Node Discrete-Time Dynamic Second Best Toll Pricing Model with a Relaxation Solution Algorithm

Dynamic congestion pricing has become an important research topic because of its practical implications. In this paper, we formulate dynamic second-best toll pricing (DSBTP) on general networks as a bilevel problem: the upper level is to minimize the total weighted system travel time and the lower level is to capture motorists’ route choice behavior. Different from most of existing DSBTP models, our formulation is in discrete-time, which has very distinct properties comparing with its continuous-time counterpart. Solution existence condition of the proposed model is established independent of the actual formulation of the underlying dynamic user equilibrium (DUE). To solve the bilevel DSBTP model, we adopt a relaxation scheme. For this purpose, we convert the bilevel formulation into a single level nonlinear programming problem by applying a link-node based nonlinear complementarity formulation for DUE. The single level problem is solved iteratively by first relaxing the strick complementarity by a relaxation parameter, which is then progressively reduced. Numerical results are also provided in this paper to illustrate the proposed model and algorithm. In particular, we show that by varying travel time weights on different links, DSBTP can help traffic management agencies better achieve certain system objectives. Examples are given on how changes of the weights impact the optimal tolls and associated objective function values.

建设智能化的上海汽车工业大厦

从智能大厦的总体结构出发，对上海汽车工业大厦的智能化系统的系统集成和各子系统进行了描述，并总结了智能化系统中的互联和联动关系。为大厦的业主在建设智能化系统时提供了参考。     

网络广告营销对汽车行业的影响

汽车网络广告营销作为高速发展的汽车产业和互联网产业结合的产物,备受广大汽车制造商的青睐,在市场上获得了巨大的成功。主要阐述了在互联网时代,网络广告在汽车行业中的作用,还分别从发展现状、存在的问题和发展对策三方面对汽车行业网络广告营销进行了分析。     

汽车协同设计模型库系统应用开发

文章结合Java关于网络数据库开发技术(SQLJ)与Pro/Engieer二次开发技术(J-Link)介绍了汽车产品模型库系统的应用开发。该系统的建立,为汽车产品的协同开发奠定了技术基础。     

使用BizTalk构建汽车行业现场打印系统

针对柔性制造汽车行业现场单据打印遇到的种种问题,探索使用微软的BizTalk Server 2006 R2进行企业内部应用集成,寻求一种通过BizTalk来对上游数据进行比对、映射、集成、处理并将消息向下游系统分发的方式,来完成一个工业级的汽车制造业现场打印系统.     

Dynamic Consumer Profiling and Tiered Pricing Using Software Agents

Shopbots or software agents that enable comparison shopping of items from different online sellers have become popular for quick and easy shopping among online buyers. Rapid searches and price comparison by shopbots have motivated sellers to use software agents called pricebots to adjust their prices dynamically so that they can maintain a competitive edge in the market. Existing pricebots charge the same price for an item from all of their customers. Online consumers differ in their purchasing preferences and, therefore, a seller's profit can be increased by charging two different prices for the same good from price-insensitive and price-sensitive consumers. In this paper, we present an algorithm that partitions the buyer population into different segments depending on the buyers' purchase criteria and then charges a different price for each segment. Simulation results of our tiered pricing algorithm indicate that sellers' profits are improved by charging different prices to buyers with different purchase criteria. Price wars between sellers that cause regular price fluctuations in the market, are also prevented when all the sellers in the market use a tiered pricing strategy.     

Dynamic Load Balancing and Pricing in Grid Computing with Communication Delay

Due to the emergence of Grid computing over the Internet, there is presently a need for dynamic load balancing algorithms which take into account the characteristics of Grid computing environments. In this paper, we consider a Grid architecture where computers belong to dispersed administrative domains or groups which are connected with heterogeneous communication bandwidths. We address the problem of determining which group an arriving job should be allocated to and how its load can be distributed among computers in the group to optimize the performance. We propose algorithms which guarantee finding a load distribution over computers in a group that leads to the minimum response time or computational cost. We then study the effect of pricing on load distribution by considering a simple pricing function. We develop three fully distributed algorithms to decide which group the load should be allocated to, taking into account the communication cost among groups. These algorithms use different information exchange methods and a resource estimation technique to improve the accuracy of load balancing. We conducted extensive simulations to evaluate the performance of the proposed algorithms and strategies.     

Dynamic Pricing for Time-Limited Goods in a Supplier-Driven Electronic Marketplace

Existing e-commerce systems employ a pull model of marketing where buyers, possibly through agents, search the e-market for suppliers offering the product of their choice. In contrast, the push model where suppliers agents approach buyers with their products, has been relatively less investigated. Push strategies are particularly appropriate for commodities that have a short shelf-life and, therefore, an elastic demand curve, allowing suppliers to exploit unexpected supply. The speed and low cost of e-commerce makes it particularly suited to the push paradigm. In this paper, we consider time-limited goods in a supplier driven marketplace that employs the push model of marketing. When constrained by a strict deadline to sell the good, the supplier uses a mobile sales agent that visits every buyer and estimates the short run demand curve of the good. At every buyer, the sales agent also employs a heuristic technique called the Maximum Returns Algorithm to recalculate the price of the good, so that the supplier can obtain the best possible gross returns from trading with the buyers. On the other hand, when the deadline to sell is not stringent, the sales agent negotiates the exchange at a point that improves both the buyers utility and the suppliers profit, as compared to the exchange point without negotiation.This research has been supported by QAD Inc. through the California Micro Program, Grants 97-122 and 98-107 and by the DARPA/ONR Grant N66001-00-1-8931.     

A Fuzzy Diagnostic Model and Its Application in Automotive Engineering Diagnosis

This paper describes a fuzzy diagnostic model that contains a fast fuzzy rule generation algorithm and a priority rule based inference engine. The fuzzy diagnostic model has been implemented in a fuzzy diagnostic system for the End-of-Line test at automobile assembly plants and the implemented system has been tested extensively and its performance is presented.     

基于动态定价策略的数据中心能耗成本优化

当前,云数据中心的能耗问题已成为业界关注的热点.已有研究工作大多致力于从技术角度降低数据中心的能耗,或在能耗与性能之间寻求一种最佳的折衷.云计算作为一种商业计算模式,已有研究成果很少考虑到云定价策略对能耗管理机制的影响.文中提出了基于动态定价策略的数据中心能耗成本优化方案.建立起服务价格和能耗成本的统一模型,通过研究两者之间的关系.协同优化服务价格与能耗成本,使数据中心的收益达到最优.鉴于数据中心规模庞大、承载任务繁重等特点,论文采用基于重载近似的大规模排队系统来对数据中心建模,根据不同数据中心间的服务需求量和电价差别,设计了多数据中心间的负载路由机制,旨在削减数据中心的整体能耗成本.针对单个数据中心,定义了双阈值策略以动态调节服务器的各种状态(On/Off/Idle等),从而使数据中心能耗成本得到进一步优化.实验结果表明,论文提出的解决方案能够在满足用户QoS需求的前提下,较好地优化数据中心能耗成本,同时使数据中心的收益达到最优.     

基于Agent的高校学费定价模型及实现

考虑经济效率和教育公平,基于多智能体系统建立高校学费定价模型,以学费对个人及其家庭高等教育选择为微观准则,以此为基础通过MAS仿真得到高等教育对社会的经济收益和从公平性反映的社会收益。社会收益值最大时对应的学费即为最优学费。最后,依据本模型实现了高校收费定价仿真系统,进行了仿真实验,得到收费定价最优值与经济效率和教育公平的关系。