多物品价格歧视拍卖模型

本文将单物品的M-参数、对数凹效用拍卖推广到多物品价格歧视拍卖.我们得到了出价函数为均衡出价函数的充要条件.     

基于NSGAII的协同产品开发项目自动协商决策

供应链环境下的协同产品开发项目中,核心企业与合作企业之间,需要对项目工期、预算和质量进行协商。科学高效的协商决策方法有助于协同产品开发项目参与各方实现双赢的协商目标。采用多Agent系统建立了协商问题的框架,构建了协商Agent以自身效用最大化和与对方建议相似度最大化为目标的多目标反建议模型;提出了基于NSGAII的自动协商决策算法,算法采用了正整数和小数混合的实数编码方式,并在遗传操作中增加了约束限制,剔除不可行个体。计算机仿真实验结果表明了算法对提高协商成功率和协商效果的有效性,说明了协商Agent可接受的最低效用值对于协商结果的影响。     

非系统风险与公司最优资本结构

公司经常面临巨大的非系统风险,而现行的资本结构理论很少涉及非系统风险对融资决策的影响.由此,基于效用无差别定价原理,运用随机控制和最优停时理论,研究由股权资本持有人决定违约时间的股权价值和债权价值,分析最优资本结构,计算最优破产策略.结果表明:适当的股权和债权的融资组合可以分散公司非系统风险,而对于谨慎型投资者,债权分散公司风险的作用减弱;投资者的风险态度对破产选择、股权价值有显著影响,对债权价值影响较小;通过实证估计绝对风险厌恶系数是一个可行的计量方法.     

基于多Agent的宏观经济智能预测决策支持系统研究

在分析智能决策支持系统的发展基础上，将人工智能思想，特别是Agent应用于构建智能宏观经济预测决策支持系统。提出面向任务的Agent设计思想，以任务为核心设计多种类型Agent共同完成预测决策任务，给出基于多Agent的系统组成结构，并给出系统中不同类型Agent的具体实现结构，同时探讨了整个系统的运行机制以及系统中多Agent之间的合作。整个系统的构建过程也是面向Agent的程序设计的过程。     

基于模糊集合论的Agent联盟生成

多Agent系统中联盟的生成是关键问题,主要研究如何在多Agent系统中构造面向任务的最优Agent联盟.对联盟生成问题作了新的描述,讨论了现有联盟生成方法的特点及不足,提出了一种基于模糊集合论的联盟生成方法.基于模糊集合论的隶属度概念,计算Agent对任务的隶属程度,并依据λ-截矩阵理论生成面向任务的Agent联盟,从而使任务由能力最适合的Agent组成的联盟来求解.实例分析说明了此方法的有效性.     

AaaS:Agent云平台研究与实现

云计算是一种通过互联网将各种资源按照一定的方法整合在一起,以服务的形式向外提供的商业模式,有着良好的发展前景.Agent技术拥有其他技术无法比拟的智能性,并在各个领域都得到了广泛的应用.但Agent软件的系统开发、部署、运行以及维护仍采用传统的技术方案,无论在硬件还是软件设施上都存在着严重的浪费,因此将云计算与Agent技术结合起来,建立基于云计算的Agent平台(AaaS),来解决上述存在的问题,利用虚拟化技术解决硬件资源的浪费,设计开发Agent开发工具箱(ADT)以统一的标准来开发和部署Agent,提供云控制器来实时监测Agent的运行状态,进而动态的解决Agent运行时存在的问题.     

基于Agent与分解协调的综合生产计划研究

以作业单元为局部决策Agent,车间管理者为全局协调Agent,引入生产节点间的内部结算价格,基于多Agent系统,建立了综合生产计划的分布式决策模型.通过将局部Agent决策目标的总和与全局Agent决策目标进行对比,证明了所引入的内部结算价格就是全局Agent目标函数关于物流平衡约束的Lagrange乘子.基于Lagrange分解协调原理,设计了局部作业单元Agent和全局协调Agent的迭代协调算法.该迭代算法以上次计算的中间结果作为对其它作业单元生产需求的估计,从而能将各个生产单元Agent的决策模型分离,实现了分布建模与求解.在算例研究中使用启发式规则来确定Lagrange乘子迭代的步长系数,保证了较好的收敛性,证明模型和算法是有效的.     

常数相对风险厌恶多单位拍卖的比较静态与定价结构

考虑竞价者具有常数相对风险厌恶时的多单位拍卖问题,讨论均衡出价与风险偏好以及价值分布之间的关系.在竞价者具有相同的风险偏好的对称拍卖情形,利用风险中性等价导出了比较静态的充要条件,这一充要条件综合了风险偏好和价值分布的变化.在竞价者具有不同的风险偏好的非对称拍卖中,导出了均衡出价关于风险偏好的线性定价结构,依据这一结构,对任意给定出价,竞价者要求的剩余是其风险厌恶参数的线性函数,并且可以分解为竞争性剩余和风险厌恶剩余.     

效用函数值的计算方法

效用函数值的计算是决策分析中的一个重要问题.由于不同决策者有不同偏好(Prefe-rence),以及同一决策者对不同抉择集合或同一抉择集合的不同子集也可能有不同偏好,故效用曲线具有近乎“捉摸不定”的多样性.多年来一直采用Standard Gamble Technique(SGT)绘制效用曲线,或按诸如边际效用递减原理等将对数函数或其它简单函数当作效用曲线,这些方法之繁琐或不严格性,使得效用理论的推广应用受到很大的局限.但也应看到,由于效用值一方面反映了决策者个人的偏好,另一方面也在一定程度上反映了决策后     

公共资本投资的随机内生增长模型

本文假设公共资本是宏观经济的一部分,由此建立一个随机内生增长模型,把公共资本作为宏观经济变量并进入个人效用.分析了经济达均衡时税收,政府投资,个人投资对经济增长率和社会福利的影响.同时还求出子最优的增长率和个人资本与财富比,消费和财富比.     

How to bid in unified second-price auctions when requests are duplicated

In display advertising auctions, a unique display opportunity may trigger many bid requests being sent to the same buyer. Bid request duplication is an issue: programmatic bidding agents might bid against themselves. In a simplified setting of unified second-price auctions, the optimal solution for the bidder is to randomize the bid, which is quite unusual. Our results motivate the recent switch to a unified first-price auction by showing that a unified second-price auction could have been detrimental to all participants.     

On the robustness of non-linear personalized price combinatorial auctions

Though the VCG auction assumes a central place in the mechanism design literature, there are a number of reasons for favoring Iterative Combinatorial Auctions (ICAs). Several promising ICA formats were developed based on primal–dual and subgradient algorithms. Prices are interpreted as a feasible dual solution and the provisional allocation is interpreted as a feasible primal solution. iBundle(3), dVSV and Ascending Proxy Auction result in VCG payoffs when the coalitional value function satisfies buyer submodularity and bidders bid straightforward, which is an ex-post Nash equilibrium in this case. iBEA and CreditDebit auctions do not even require the buyer submodularity and achieve the same properties for general valuations. Often, however, one cannot assume straightforward bidding and it is not clear from the theory how these non-linear personalized price auctions (NLPPAs) perform in this case. Robustness of auctions with respect to different bidding behavior is a critical issue for any application. We conducted a large number of computational experiments to analyze the performance of NLPPAs with respect to different bidding strategies and valuation models. We compare NLPPAs with the VCG auction and with ICAs with linear prices, such as ALPS and the Combinatorial Clock Auction. While NLPPAs performed very well in case of straightforward bidding, we observe problems with revenue, efficiency, and speed of convergence when bidders deviate.     

Reverse auction with buyer-supplier negotiation using bi-level distributed programming

This study presents a framework for solving a sealed-bid, multi-issue, and multi-sourcing reverse auction problem in which negotiation takes place between the buyer and the suppliers during the bidding process. The problem is formulated as a bi-level distributed programming model in which the buyer is the upper level decision maker, while suppliers at the lower level make decisions independent of each other. The negotiation process between the buyer and the suppliers is facilitated via the iterative exchange of decision information between the upper and lower levels of the model. The outcome of the sealed-bid auction is determined using an algorithm designed to establish the optimum quantity allocation and delivery time at the upper level and the corresponding optimized production plans at the lower level. The feasibility of the proposed approach is demonstrated via an illustrative example.     

基于改进数据包络分析的建设工程评标模型

建设工程评标是一项复杂的系统工程.为建立合理的评标决策支持系统,根据实际评标建立以商务标为目标函数,以技术标为约束条件的评标模型.引入数据包络分析(DEA)方法,建立第二目标函数为决策单元非效率值总和最小模型,进行交叉评价,解决了CCR模型在实际应用中不能完全确定中标顺序的问题.通过实际案例分析,交叉评价模型能够产生独立效率值并进行有效排序,证明了评标模型的可操作性与适用性.     

Buyer behavior adaptation based on a fuzzy logic controller and prediction techniques

The current form of Web provides numerous product resources available to users. Users can rely on intelligent agents for purchase actions. These actions are taken in specific environments such as Electronic Markets (EMs). In this paper, we study the interaction process between buyers and sellers and focus on the buyer side. Each buyer has the opportunity to interact with a number of sellers trying to buy the most appropriate products. This interaction can be modeled as a finite horizon Bargaining Game (BG). In this game, players have opposite goals concerning the product price. We adopt a number of techniques in the buyer side trying to give the appropriate level of efficiency in the buyer decision process. The buyer uses a prediction mechanism in combination with the use of Fuzzy Logic (FL) theory in order to be able to predict the upcoming seller proposal and, thus, understand the seller pricing policy. Based on this, he/she can adapt his/her behavior when trying to purchase products. The buyer adaptation mechanism produces the belief that the buyer has about the seller pricing policy and a parameter that indicates his/her own pricing policy which yields the buyer offers in the upcoming rounds. Moreover, the buyer is based on FL system that derives the appropriate actions at every round of the BG. Our results show that the combination of Fuzzy Logic (FL) with the above-mentioned techniques provides an efficient decision mechanism in the buyer side that in specific scenarios outperforms an optimal stopping model.     

Optimal Risk-Sharing When Risk Preferences are Uncertain

In many cases, a firm or agency needs a product that only one vendor can supply and for which the final cost is uncertain. An optimal risk-sharing arrangement is sought when the buyer and contractor agree on the probability distribution of cost but the buyer is uncertain of the contractor's risk-preferences. We find that when the buyer and contractor have exponential utilities, the optimal profit arrangement for the higher risk-averse contractor is no longer linear but concave in the costs. The degree of concavity is affected by the probabilistic beliefs on the contractor's risk-preferences. As the more risk-averse contractor becomes more likely, her chosen profit arrangement becomes less concave approaching the ideal, linear arrangement. The less risk-averse contractor is provided a profit arrangement with a certainty equivalent above her reservation price. This is the price the buyer must pay in order to entice a less risk-averse contractor into agreeing to accept a more risky profit arrangement.Another formulation is considered that assumes the buyer and contractor maximize approximations to their certainty equivalents in order to provide a more practical and possibly viable approach to sole-source contracting.     

Optimizing delivery lead time/inventory placement in a two-stage production/distribution system

In this paper we study a system composed of a supplier and buyer(s). We assume that the buyer faces random demand with a known distribution function. The supplier faces a known production lead time. The main objective of this study is to determine the optimal delivery lead time and the resulting location of the system inventory. In a system with a single-supplier and a single-buyer it is shown that system inventory should not be split between a buyer and supplier. Based on system parameters of shortage and holding costs, production lead times, and standard deviations of demand distributions, conditions indicating when the supplier or buyer(s) should keep the system inventory are derived. The impact of changes to these parameters on the location of system inventory is examined. For the case with multiple buyers, it is found that the supplier holds inventory for the buyers with the smallest standard deviations, while the buyers with the largest standard deviations hold their own inventory.     

Generalized lot sentencing rule for estimating the value of production lot for sale

In the traditional lot sentencing rule, a buyer arrives to one of two decisions regarding lot disposition; either accept or reject a lot. However, it is more appropriate to consider choices between those two extreme decisions. A clear case where the traditional lot sentencing rule is not flexible is when a buyer purchases a lot from an English auction. In this paper, we propose a model that helps a buyer in estimating the value of a production lot. This model can be used by a bidder before the bidding process starts to estimate the value of an auctioned lot. The model provides an action plan that includes the estimated acquisition cost as a function of the number of defective items found in a random sample. Unlike the traditional lot sentencing rule, the proposed rule is more flexible and provides buyers with wider range of possible actions.     

Global optimal policy for vendor–buyer integrated inventory system within just in time environment

Traditionally, inventory problems for the vendor and the buyer are treated separately. In modern enterprises, however, the integration of vendor–buyer inventory system is an important issue. This co-operative approach to inventory management contributes to the success of supply chain management by minimizing the joint inventory cost. The joint inventory cost and the response time can further be reduced when the buyer orders and the vendor replenishes the required items just in time (JIT) for their consumption. The inclusion of the JIT concept in this model contributes significantly to a joint inventory cost reduction. A numerical example and sensitivity analysis are carried out. The derived results show an impressive cost reduction when compared with Goyal’s model.     

招标采购中的采购物品打包模型及其优化算法

招标采购是采购物品(货物或服务)的有效方式, 采购物品打包是招标采购的重要环节并对采购绩效有重要影响。采购物品打包是确定一组互斥的采购包集合, 在充分的市场竞争条件下购买全部采购物品, 且每个采购包的候选供应商应对该采购包中的所有物品进行投标。目前采购物品打包问题的研究文献较少, 本文通过定义采购包和采购打包方案等概念, 建立了采购物品打包问题的0-1整数规划模型。由于该模型具有NP-hard特征, 为此首先将其转化为旅行商问题, 并基于遗传算法设计采购物品打包问题的求解算法。实验表明:与整数规划求解软件和双聚类算法相比, 本文所提出的算法在解决采购物品打包问题时具备更好的优化性能和计算效率。