基于价格歧视策略的多单元逆向多属性英式拍卖机制

针对现有的多单元逆向多属性拍卖机制的市场分配效率都比较低,不利于社会效益最大化和采购双方长期合作等问题,设计了高效率的基于价格歧视策略的多单元逆向多属性英式拍卖机制,利用线性混合整数规划建立了赢者确定模型,并基于新建立的拍卖机制给出了拍卖流程和投标策略,为供应商提供投标决策支持。然后通过设计数值实例和对比模拟实验收集数据,采取统计分析的方法验证了新设计的拍卖机制市场分配效率和采购方的效益都比较高。上述研究结果适用于通过逆向多属性拍卖与信息技术相结合的网上自动化多单元商品采购。     

基于可靠度确定属性权重的三角模糊数多属性决策方法

针对三角模糊数多属性决策中的属性权重确定问题,从属性维度和方案维度分别考量决策信息的相似度差异指标和不确定性指标,提出了一种基于可靠度确定属性权重的方法。并结合三角模糊数可能度比较关系理论给出了完整的决策步骤,最后通过实例应用和对比分析,验证了所提方法的有效性和可行性,为此类问题的科学决策拓展了思路。     

不确定多属性决策中的一种模糊赋权方法

研究了以三角模糊数给出属性权重的不确定多属性决策问题,提出了一种基于三角模糊数的赋权方法,并给出了决策模型.首先决策者将属性权重两两比较的结果用三角模糊数表示,构造三角模糊数互补判断矩阵.通过求解矩阵得到模糊权重.然后,集结各方案的模糊综合属性值,通过构造并求解可能度矩阵对方案进行排序.最后给出了一个应用实例.     

反向拍卖的一种在线定价策略及竞争分析

本文讨论了网络环境下从众多投标的供应商那里选择一家供应商来购进所需商品的反向拍卖,提出了一种考虑了买家起始价格和最高忍耐价格的在线定价策略,该在线定价策略利用了市场的价格信息,克服了由单一定价造成的完不成采购任务或不必要的成本浪费等缺陷,对该在线定价策略进行了竞争分析并得到了最优的竞争比。最后,通过实例说明本文提出的在线定价策略的可操作性。     

基于集对分析联系数的信息不完全直觉模糊多属性决策

信息不完全直觉模糊多属性决策是一类不确定性决策问题,其不确定性来自属性权重信息不完全和属性值的直觉模糊数表示.为了系统地刻画直觉模糊多属性决策中的不确定性,避免直觉模糊多属性决策中利用得分函数做决策的片面性和不准确性,可以将信息不完全的权重和直觉模糊数表示的属性值转化成集对分析理论中的联系数,并建立信息不完全直觉模糊多属性决策模型,通过对不确定性进行分析后作出决策.实例应用表明该决策方法具有合理性和可行性.     

基于模糊理论的软件寿命周期费用评价模型

软件寿命周期费用评价模型涉及到软件开发、使用和维护过程中各种资源最有效利用的权衡分析。由于软件开发不是一门严谨的精确科学,往往存在大量具有不确定性的需求以及许多未知和不确定因素,所有这些都给软件寿命周期费用评价带来模糊效用。本文将模糊理论应用于软件寿命周期费用的评价,给出了从评价属性模糊值的确定、模糊评价模型的建立,到模型求解和最优方案选择的模糊评价方法,并通过对一个算例的分析,证明了该模型的可行性。     

不确定区间隶属度语言变量及其应用

基于不确定语言变量和区间模糊数,提出了不确定区间隶属度语言变量的概念,定义了不确定区间隶属度语言变量的运算规则、大小比较方法,给出了不确定区间隶属度语言变量的加权算术平均算子、加权几何平均算子及其相应性质,并将这些算子应用于属性权重确知且属性值以不确定区间隶属度语言变量形式给出的不确定多属性群决策问题中,通过示例验证了基于不确定区间隶属度语言变量信息的多属性群决策方法的有效性和可行性。     

基于集对分析的多种不确定偏好形式大群体决策方法

针对具有多种不确定偏好形式的多方案大群体决策问题,提出一种基于集对分析的群决策方法。将区间数、三角模糊数以及语言值三种形式的不确定偏好转换为联系数,保留了不确定偏好信息中的确定性与不确定性。提出一种区间聚类算法,在决策成员权重未知的情况下对成员进行赋权。利用加权综合联系数对大群体偏好进行集结,根据方案的集对势大小给出方案的排序。该方法避免了确定权重时的主观性,同时考虑决策信息的确定性与不确定性,提高了决策结果的可信度。通过实例分析验证了方法的有效性和实用性。     

无限可分商品在线反向拍卖的风险策略研究

对网络环境下一个买家多个卖家的反向拍卖,研究了供应商在不同时间到达并投标而采购商接到每个投标后需要立即做出决策的在线反向拍卖的风险策略。对于无限可分商品,在资金一定前提下,首先对采购商无风险行为情形给出了基于标价上涨威胁的在线反向拍卖策略,通过竞争分析得到了其最优竞争比及整体需要曲线;其次引入采购商的风险容忍度概念,建立了激励相容在线反向拍卖的风险回报框架,并对风险忍耐策略进行了竞争分析。     

基于信息量的不确定型多属性决策方法

针对属性值为区间数的不确定型多属性决策问题进行了研究,给出了属性值满意度的概念和考虑风险系数的满意度评价函数计算方法;重定义了公理设计理论的信息量概念,提出了基于信息量的不确定多属性决策方案排序方法,为解决不确定型多属性决策问题提供了一种简单实用的方法。最后利用实例计算了验证了方法的有效性和可行性。     

Configurable offers and winner determination in multi-attribute auctions

The theory of procurement auctions traditionally assumes that the offered quantity and quality is fixed prior to source selection. Multi-attribute reverse auctions allow negotiation over price and qualitative attributes such as color, weight, or delivery time. They promise higher market efficiency through a more effective information exchange of buyer’s preferences and supplier’s offerings. This paper focuses on a number of winner determination problems in multi-attribute auctions. Previous work assumes that multi-attribute bids are described as attribute value pairs and that the entire demand is purchased from a single supplier. Our contribution is twofold: First, we will analyze the winner determination problem in case of multiple sourcing. Second, we will extend the concept of multi-attribute auctions to allow for configurable offers. Configurable offers enable suppliers to specify multiple values and price markups for each attribute. In addition, suppliers can define configuration and discount rules in form of propositional logic statements. These extensions provide suppliers with more flexibility in the specification of their bids and allow for an efficient information exchange among market participants. We will present MIP formulations for the resulting allocation problems and an implementation.     

制造商为小本经营情况下零售商购货机制的合同设计

考虑零售商采用逆向拍卖方式到个小本经营的制造商处购货,研究供应链中如何设计合同使得零售商单位时间的支出费用最低,采用最优控制的方法和委托代理理论中的显示原理,得出零售商的最优购货机制,同时给出两个简单的购货机制——打分拍卖机制和固定生产时间下的价格拍卖。结果表明由制造商承担的制造费用越多,零售商的进货价格越高;在简单机制下,制造商承担制造费用的大小并不影响最优生产率的制定。     

基于高斯分布的在线采购机制设计及竞争分析

依附于互联网电子商务的在线采购拍卖交易, 对传统的贝叶斯离线拍卖理论提出新的挑战, 因为面对不同时间点的投标, 采购电商必须即可决策出是否中标以及购买价格。鉴于此, 对于诸如石油、煤、粮食等无限可分商品的电子采购, 本文基于投标具有高斯分布特征设计了一种激励相容的在线采购策略, 演绎出在线采购的数学模型, 利用Runge-Kutta数值算法, 通过Matlab编程求解出采购电商在线定价策略的需求曲线及其对应的竞争比, 最后, 利用数值模拟, 将在线采购机制策略与纯竞争分析得到的在线采购策略比较, 结果显示利用了高斯分布信息的在线采购策略的竞争性能由于利用了投标的统计信息而得到了提高。     

Multi-criteria auctions without full comparability of bids

The emergence of auction mechanisms that support bids characterized by several attributes is one of the most recent evolutions within auction theory. These mechanisms, referred to as multi-attribute, multiple issue or multi-dimensional auctions, are at the intersection between multi-criteria decision and auction theories. The purpose of this paper is to introduce multi-criteria auctions the originality of which is not to require full comparability between bids. We claim that this distinctive feature is of great interest, especially in procurement situations. Furthermore, the existence of potential incomparability between multi-dimensional offers will permit us to manage different bidding niches coexisting within the same bidding space. A theoretical framework based on a general preference structure will be introduced and then referenced to existing approaches such as multi-attribute auctions or new ones such as dominance based multi-criteria auctions or butterfly auctions.     

A multi-attribute e-auction mechanism for procurement: Theoretical foundations

We describe a multi-attribute e-auction mechanism, with a focus on its theoretical foundations. Our mechanism is designed for auctioning multiple units of a good, primarily in B2B transactions. It can be used in various types of forward and reverse auctions/RFQs (Request for Quote), although the emphasis in this paper is on procurement. To incorporate the auction owner’s preferences across issues/attributes in an auction/negotiation setting, we adopt a novel application of the ‘pricing out’ technique. Another key feature of our mechanism is the optimization-based ‘suggested price’ decision support component, which momentarily gives the best price acceptable to the buyer.     

基于前景理论和三角模糊MULTIMOORA的多阶段决策方法

针对时间权重与属性权重完全未知的三角模糊多属性决策问题,基于前景理论和MULTIMOORA提出一种新的决策方法。首先,建立备选方案在不同时段的三角模糊前景决策矩阵,根据时间度及不同时段内备选方案前景值的差异构建时间权重优化模型,并运用最大偏差法的基本思想获得属性权重。其次,基于三角模糊数提出一种新的MULTIMOORA扩展形式,并结合占优理论对备选方案进行比选。最后,通过实例证明了所提方法是可行的,也是有效的。     

基于模糊语言评估和联系数的多属性群决策方法

对方案的属性评估信息以模糊语言形式给出的多属性群决策问题,采用集对分析理论进行处理,提出了一种基于模糊语言评估和联系数的多属性群决策方法,实例应用表明了该方法的有效性和实用性.     

Carrier assignment models in transportation procurement

This paper extends carrier assignment models used in winner determination auctions for transportation procurement to include shipper non-price objectives and carrier transit point costs. The models are unlike traditional carrier assignment models which incorporate only carrier lane bids, and different from combinatorial auction models which focus on packets of lanes without considering transit point costs. We develop solutions, including metaheuristics, for the new models and through computational experimentation show that the algorithms work well and can be easily implemented.     

Reputation-based winner determination problem for combinatorial transportation procurement auctions

This paper proposes a reputation-based winner determination problem for transportation procurement auctions where the allocation of long-term contracts to carriers is decided with respect to both bid ask-prices and carriers reputation. The objective is to manage the trade-off between transport costs and the quality of service during operations. Carriers reputation is translated into unexpected hidden cost that represents the possible additional cost that the shipper may incur when dealing with a set of winning carriers. This cost depends essentially on the carriers reputation as evaluated by the shipper running the auction. To evaluate carriers reputations, the shipper uses a number of service attributes with different weights depending on shipping contracts.