A generic auction algorithm for the minimum cost network flow problem

In this paper we broadly generalize the assignment auction algorithm to solve linear minimum cost network flow problems. We introduce a generic algorithm, which contains as special cases a number of known algorithms, including the -relaxation method, and the auction algorithm for assignment and for transportation problems. The generic algorithm can serve as a broadly useful framework for the development and the complexity analysis of specialized auction algorithms that exploit the structure of particular network problems. Using this framework, we develop and analyze two new algorithms, an algorithm for general minimum cost flow problems, called network auction, and an algorithm for thek node-disjoint shortest path problem.     

基于智能竞标的自适应轨压控制算法

设计了一种应用于高压共轨柴油发动机的轨压控制算法。算法采用组合竞拍机制以解决复合工况下的轨压扰动问题,并设计了一种分段动态标定算法以解决传统PID标定算法计算效率低的问题,此外算法针对柴油发动机特性对PID控制器进行了多项改进以提高算法响应速度和跟随性。最后通过仿真实验对算法进行了验证,实验结果证明本算法对输入转速信号及喷油期望值具有良好的跟随性和响应速度,并且轨压控制较为平稳,其波动幅度不超过1%,基本符合高压共轨柴油发动机正常工作的需要。     

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。     

拍卖市场上不同经验类型竞价者竞价行为研究

研究公共价值拍卖市场上不同经验类型竞价者的竞价行为.根据拍卖经验的不同可以把竞价人分成两类:天真者和理性者.通过建立"天真-理性"的竞价模型,分析了天真者与理性者最优出价策略,得到了在价值信号均匀分布情况下,天真者的事前期望支付大于理性者的事前期望支付;并得到了天真者的进化比例.     

Polynomial auction algorithms for shortest paths

In this paper we consider strongly polynomial variations of the auction algorithm for the single origin/many destinations shortest path problem. These variations are based on the idea of graph reduction, that is, deleting unnecessary arcs of the graph by using certain bounds naturally obtained in the course of the algorithm. We study the structure of the reduced graph and we exploit this structure to obtain algorithms withO (n min{m, n logn}) andO(n ²) running time. Our computational experiments show that these algorithms outperform their closest competitors on randomly generated dense all destinations problems, and on a broad variety of few destination problems.Research supported by NSF under Grant No. DDM-8903385, by the ARO under Grant DAAL03-86-K-0171, by a CNR-GNIM grant, and by a Fullbright grant     

关于研发机构非显著工艺创新的最优许可研究

研发机构创新成功后,应该重视知识资产的主动管理,在专利许可谈判中科学合理地确定专利许可策略,以追求收益最大化.本文的目的是进一步完善与具体化Kamien,Tauman与Oren(1992)的模型,深入研究研发机构在不同许可机制下对在位厂商的非显著创新许可收益,以及最优许可策略选择.主要结论是:给定厂商数量,当创新规模较小时,研发机构的最优策略为提成许可,其次是不限许可数量的F(F)许可与一级价格密封投标拍卖许可;当创新规模较大时,研发机构的最优策略为拍卖许可,提成许可次之,最后是不限许可数量的F(F)许可.     

基于Java APplet的Internet地图服务平台设计

;主要论述了网络环境下建立地图服务平台的设计思路与结构设计.在此基础上对矢量地图数据基本流程做了详细的论述,其中主要包括数据获取、数据压缩、数据传输、数据表达与空间查询等.基于Java语言.论文从底层实现了基于socket协议连接的服务器端与客户端地图数据的组织、传输与数据可视化表达,实现了网络地图发布平台.论文主要讨论了Java环境下具体地图服务平台设计.     

On Heuristics for Solving Winner Determination Problem in Combinatorial Auctions

The winner determination problem (WDP) in combinatorial auctions is the problem of, given a finite set of combinatorial bids B, finding a feasible subset B of B with a maximum revenue. WDP is known to be equivalent to the maximum weight set packing problem, and hard to approximate by polynomial time algorithms. This paper proposes three heuristic bid ordering schemes for solving WDP; the first two schemes take into account the number of goods shared by conflicting bids, and the third one is based on a recursive application of such local heuristic functions. We conducted several experiments to evaluate the goodness of the proposed schemes. The result of experiments implies that the first two schemes are particularly effective to improve the performance of the resulting heuristic search procedures. More concretely, they are scalable compared with the conventional linear programming (LP) relaxation based schemes, and could quickly provide an optimum solution under optimization schemes such as the branch-and-bound method. In addition, they exhibit a good anytime performance competitive to the LP-based schemes, although it is sensitive to configurable parameters controlling the strength of contributions of bid conflicts to the resultant bid ordering schemes.     

Revenue deficiency under second-price auctions in a supply-chain setting

Consider a firm, called the buyer, that satisfies its demand over two periods by assigning both demands to a supplier via a second-price procurement auction; call this the Standard auction. In the hope of lowering its purchase cost, the firm is considering an alternative procedure in which it will also allow bids on each period individually, where there can be either one or two winners covering the two demands; call this the Multiple Winner auction. Choosing the Multiple Winner auction over the Standard auction can in fact result in a higher cost to the buyer. We provide a bound on how much greater the buyer’s cost can be in the Multiple Winner auction and show that this bound is tight. We then sharpen this bound for two scenarios that can arise when the buyer announces his demands close to the beginning of the demand horizon. Under a monotonicity condition, we achieve a further sharpening of the bound in one of the scenarios. Finally, this monotonicity condition allows us to generalize this bound to the T-period case in which bids are allowed on any subset of period demands.     

Robust strategic bidding in auction-based markets

In this paper, we propose an alternative methodology for devising revenue-maximizing strategic bids under uncertainty in the competitors’ bidding strategy. We focus on markets endowed with a sealed-bid uniform-price auction with multiple divisible products. On recognizing that the bids of competitors may deviate from equilibrium and are of difficult statistical characterization, we proposed a two-stage robust optimization model with equilibrium constraints aiming to devise risk-averse strategic bids. The proposed model is a trilevel optimization problem that can be recast as a particular instance of a bilevel program with equilibrium constraints. Reformulation procedures are proposed to find a single-level equivalent formulation suitable for column-and-constraint generation (CCG) algorithm. Results show that even for the case in which an imprecision of 1% is observed on the rivals’ bids in the equilibrium point, the robust solution provides a significant risk reduction (of 79.9%) in out-of-sample tests. They also indicate that the best strategy against high levels of uncertainty on competitors’ bid approaches to a price-taker offer, i.e., bid maximum capacity at marginal cost.