Numerical calculation of an asymmetric supply function equilibrium with capacity constraints

Producers submit offer curves to a procurement auction, e.g. an electricity auction, before uncertain demand has been realised. In the supply function equilibrium (SFE), every firm commits to the offer curve that maximises its expected profit, given the offer curves of competitors. The equilibrium is given by a system of differential equations. In practice, it has been very difficult to find valid SFE, i.e. non-decreasing solutions, from this system, especially for asymmetric producers. This paper shows that valid SFE can be calculated by means of a shooting algorithm that combines numerical integration with an optimisation procedure that searches for an end-condition. Multiple/parallel shooting is used for ill-conditioned cases.     

The stochastic bid generation problem in combinatorial transportation auctions

In this paper, we deal with the generation of bundles of loads to be submitted by carriers participating in combinatorial auctions in the context of long-haul full truckload transportation services. We develop a probabilistic optimization model that integrates the bid generation and pricing problems together with the routing of the carrier’s fleet. We propose two heuristic procedures that enable us to solve models with up to 400 auctioned loads.     

First- and second-price sealed-bid auctions applied to push and pull supply contracts

We investigate a newsvendor-type retailer sourcing problem under demand uncertainty who has the option to source from multiple suppliers. The suppliers’ manufacturing costs are private information. A widely used mechanism to find the least costly supplier under asymmetric information is to use a sealed-bid reverse auction. We compare the combinations of different simple auction formats (first- and second-price) and risk sharing supply contracts (push and pull) under full contract compliance, both for risk-neutral and risk-averse retailer and suppliers. We show the superiority of a first-price push auction for a risk-neutral retailer. However, only the pull contracts lead to supply chain coordination. If the retailer is sufficiently risk-averse, the pull is preferred over the push contract. If suppliers are risk-averse, the first-price push auction remains the choice for the retailer. Numerical examples illustrate the allocation of benefits between the retailer and the (winning) supplier for different number of bidders, demand uncertainty, cost uncertainty, and degree of risk-aversion.     

基于改进的粗糙集条件信息熵和灰关联投影法的工程项目投标决策研究

投标决策是建筑企业面临的一大难题.在分析建设工程投标风险因素的基础上,提出一种基于改进的粗糙集条件信息熵和灰关联投影法的投标决策方法.文中投标风险因素的客观权重经两次修正,更具全面性和合理性;然后结合依靠专家经验确定的主观权重得到综合权重;最后将综合权重应用于灰关联投影法进行投标决策.通过应用实例,验证决策方法的可操作性和合理性,为承包商实际的投标工作提供一定的借鉴和参考.     

Post-objective determination of weights of the evaluation factors in public procurement tenders

In public procurement tenders the awarding criterion of the most economically advantageous bid employs weights to aggregate the numerical scores assigned to each proposal with respect to different evaluation factors. Typically these weights are fixed and subjectively set in advance. Methods, which objectively determine the weights after the opening of the sealed bids on the basis of the most or least favorable weights for each proposal, are developed. Post-objective methods of weight determination are shown to enhance the integrity of the evaluation process and to limit corruption in a public tender. The connection of Data Envelopment Analysis, which has been extensively applied to measure supplier efficiency, with the developed methods, is explored. Average least and most favorable weights are derived and optimal bidding strategies in this setting are presented.     

Dynamic lot-sizing in sequential online retail auctions

Retailers often conduct non-overlapping sequential online auctions as a revenue generation and inventory clearing tool. We build a stochastic dynamic programming model for the seller’s lot-size decision problem in these auctions. The model incorporates a random number of participating bidders in each auction, allows for any bid distribution, and is not restricted to any specific price-determination mechanism. Using stochastic monotonicity/stochastic concavity and supermodularity arguments, we present a complete structural characterization of optimal lot-sizing policies under a second order condition on the single-auction expected revenue function. We show that a monotone staircase with unit jumps policy is optimal and provide a simple inequality to determine the locations of these staircase jumps. Our analytical examples demonstrate that the second order condition is met in common online auction mechanisms. We also present numerical experiments and sensitivity analyses using real online auction data.     

Influence diagrams for Bayesian decision analysis

Influence diagrams for representing Bayesian decision problems are redefined in a formal way using conditional independence. This makes the graphs somewhat more helpful for exploring the consequences of a clients state beliefs. Some important results about the manipulation of influence diagrams are extended and reviewed as is an algorithm for computing an optimal policy. Two new results about the manipulation of influence diagrams are derived. A novel influence diagram representing a practical decision problem is used to illustrate the methodologies presented in this paper.     

物业管理招标中的层次关联比选

应用层次分析法确定影响物业管理投标书总体方案的各因素间权重 ,根据灰色关联理论建立了对投标书进行总体综合评价并排序优选的数学模型 ,给出了计算实例 .     

Spying on the cost structure of naive bidding competitors via linear programming models

A linear programming model is constructed which enables a firm to estimate its competitor's cost structure when the competitor adheres to a non-randomized strategy. The existence of the model makes randomized bidding prudent apart from game theory considerations. The need for increased curriculum attention to optimal bidding is highlighted.     

基于MAS协作机制的动态计算资源调度模型

针对网格环境的自治性、动态性、分布性和异构性等特征.提出基于多智能体系统(Mutil Agent System,MAS)博弈协作的资源动态分配和任务调度模型,建立了能够反映供求关系的网格资源调度模型和任务求解算法,证明了资源分配博弈中Nash均衡点的存在性、唯一性和Nash均衡解,该方法能够利用消费者agent的学习和协商能力,考虑和引入消费者的心理行为,使得消费者的资源申请和任务调度具有较高的合理性和有效性.实验结果表明,资源调度算法不但可以有效减少不必要的延迟,而且在响应时间的平滑性、吞吐率及资源利用率方面比传统算法要好,从而使得整个资源的供需合理、负载均衡.