Truthful approximation mechanisms for restricted combinatorial auctions

When attempting to design a truthful mechanism for a computationally hard problem such as combinatorial auctions, one is faced with the problem that most efficiently computable heuristics can not be embedded in any truthful mechanism (e.g. VCG-like payment rules will not ensure truthfulness).We develop a set of techniques that allow constructing efficiently computable truthful mechanisms for combinatorial auctions in the special case where each bidder desires a specific known subset of items and only the valuation is unknown by the mechanism (the single parameter case). For this case we extend the work of Lehmann, O'Callaghan, and Shoham, who presented greedy heuristics. We show how to use If-Then-Else constructs, perform a partial search, and use the LP relaxation. We apply these techniques for several canonical types of combinatorial auctions, obtaining truthful mechanisms with provable approximation ratios.     

Computationally-feasible truthful auctions for convex bundles

In many economic settings, like spectrum and real-estate auctions, geometric figures on the plane are for sale. Each bidder bids for his desired figure, and the auctioneer has to choose a set of disjoint figures that maximizes the social welfare. In this work, we design mechanisms that are both incentive compatible and computationally feasible for these environments. Since the underlying algorithmic problem is computationally hard, these mechanisms cannot always achieve the optimal welfare; Nevertheless, they do guarantee a fraction of the optimal solution. We differentiate between two information models—when both the desired figures and their values are unknown to the auctioneer or when only the agents' values are private data. We guarantee different fractions of the optimal welfare for each information model and for different families of figures (e.g., arbitrary convex figures or axis-aligned rectangles). We suggest using a measure on the geometric diversity of the figures for expressing the quality of the approximations that our mechanisms provide.     

基于遗传算法的排水管道费用函数优化

在常见排水管道费用函数模型的基础上,通过引入0-1变量构造了通用的排水管道费用函数公式,并采用改进遗传算法进行了参数优化,有效地提高了程序的通用性和效率,可用于快速确定不同地区的最佳排水管道费用函数。     

Multiplicity and complexity issues in contemporary production scheduling

High multiplicity scheduling problems arise naturally in contemporary production settings where manufacturers combine economies of scale with high product variety. Despite their frequent occurrence in practice, the complexity of high multiplicity problems – as opposed to classical, single multiplicity problems – is in many cases not well understood. In this paper, we discuss various concepts and results that enable a better understanding of the nature and complexity of high multiplicity scheduling problems. The paper extends the framework presented in Brauner et al. [ Journal of Combinatorial Optimization (2005 ) Vol. 9, pp. 313–323] for single machine, non-preemptive high multiplicity scheduling problems, to more general classes of problems.     

基于遗传算法的多周期确定性IRP问题研究

本文主要通过在分析多周期确定性条件的基础上建立的数学模型,研究多周期确定性客户需求下的IRP问题,并利用遗传算法对模型进行求解.同时以小群体规模、指定交叉率和变异率为实例,进行数值模拟实例分析.与利用经济批量采购公式求解的客户补货量进行了对比分析,遗传算法可以有效地解决了IRP中最优补货量的问题.     

一种不确定环境下供应链的模型与算法

供应链管理作为一种新型的企业关系管理模式在现代市场竞争中为企业生存与发展提供了一种工具。本文针对不确定环境下供应链的优化进行了研究。给出了一个供应链的仿真模型及其优化算法。     

Measuring the impact of R&;D on Productivity from a Econometric Time Series Perspective

In this paper we argue that the standard sequential reduction approach to modelling dynamic relationships may be sub-optimal when long lag lengths are required and especially when the intermediate lags may be less important. A flexible model search approach is adopted using the insights of Bayesian Model probabilities, and new information criteria based on forecasting performance. This approach is facilitated by exploiting Genetic Algorithms. Using data on U.K. and U.S. agriculture the bivariate time series relationship between R&D expenditure and productivity is analysed. Long lags are found in the relationship between R&D expenditures and productivity in the U.K. and in the U.S. which remain undiscovered when using the orthodox approach. This finding is of particular importance in the debate on the optimal level of public R&D funding.JEL Classification: C22, C51, Q16     

基于遗传算法的包装废弃物回收逆向供应链网络构建研究

随着人们对生态环保和经济可持续发展的进一步认识,面对可再利用包装废弃物资源的浪费和对环境造成的污染,越来越多的人们意识到包装废弃物回收的重要性。文章分析了国内包装废弃物回收的现状,提出了包装废弃物回收的逆向供应链网络模型,利用遗传算法,对模型进行了优化求解,并给出了算例。     

基于多台自动导引运输车的自动分拣系统

为了提高仓储系统中物流分拣的效率,设计了一套基于多台自动导引运输车（AGV）的自动分拣系统。首先将整个系统分解为硬件部分和软件部分,硬件部分主要包含服务器、多台AGV和机械手等等,软件部分的设计主要包含智能调度算法设计、最短路径算法设计和多AGV之间的避障算法设计等等;之后,通过逐步完成上述子模块的设计工作,即可完成整个系统的设计。经过在工厂一段时间的试运行,实践结果表明,该套系统的设计能够完成多台AGV的调度,并较大地提高了物流分拣的效率。     

超混沌视频加密系统的FPGA设计与实现

随着多媒体技术的不断发展，视频信息安全愈发受到人们的关注。为解决视频信息的安全问题，提出了一种基于现场可编程门阵列(FPGA)技术的超混沌视频加密方法。在加密过程中，一方面FPGA控制数字摄像头实现实时彩色视频信息的采集；另一方面，在计算机密钥指令下，利用FPGA使超混沌系统产生有效的伪随机序列，实现对所采集视频信息的数据和地址的双重超混沌加密。给出了具体的超混沌视频加密算法和设计流程以及FPGA实现结果。安全性分析表明，明密文主观视觉对比显著不同，密钥空间大，视频图像统计特性的相关性弱，说明基于FPGA的超混沌视频加密系统加密效果良好可靠。