电子中介中的交易匹配研究

研究电子中介中的匹配问题,提出了电子中介处理多属性商品交易时双方的满意度函数.以最大化双方满意度为目标,建立了多个买家和多个卖家各交易一件同类商品的多目标匹配优化模型,提出一种求解单目标的优先贪婪算法.3种算法的仿真实验表明,优先贪婪算法比精确算法损失匹配数量约8.0%,节约时间约31.6%;比标准贪婪算法提高匹配数量约2.7%,节约时间约36.3%.     

电子中介中的多属性匹配研究

研究了电子中介处理个人之间单件物品交易时的多属性匹配问题。建立了多目标匹配模型,推导了用理想点法求解该模型时,求解其一次距离最小等价于求解原各目标相应系数直接相加所得的单目标指派问题。用有指导随机搜索算法求解了距理想点的二次距离最小。仿真实验表明,变量规模小于65时可以求二次距离最小并得到满意解;而大于65时求一次距离最小更为合适。     

中介视角下供需匹配决策方法研究

供需匹配是优化资源利用、形成长期稳定伙伴关系的关键，其本质是寻找或选择合适的供需合作方案。研究针对中介视角下多种货物的供需匹配问题，考虑供应企业关于交易价格的满意度、需求企业关于交易价格和偏好序的满意度、中介视角下供需方各主体的重要程度，以最大化加权供、需方满意度为目标函数，以交易中的具体限制为约束条件，建立基于中介视角的供需匹配多目标决策模型。根据研究问题特点，设计改进的自适应遗传算法对匹配模型求解。以煤矿、煤炭需求企业、港口三方主体间多种煤炭的供需匹配问题为例进行实证研究，计算获得港口视角下供需企业的匹配方案，说明所建立模型和算法的可行性与有效性，能够为客户关系管理研究与应用提供参考与指导。     

图结构在航空遥感图像特征点匹配中的应用

为了解决海上航空遥感图像拍摄目标及相机视角变化快,相似特征多导致的匹配不一致问题,并提高匹配算法的效率,提出了一种基于图结构的航空遥感图像特征点匹配算法。该特征匹配过程分为初始匹配和精确匹配两步,首先采用快速特征提取算法SURF进行特征提取并进行初始匹配,然后在精确匹配过程中充分考虑图像的局部空间结构及全局信息,建立[K]近邻图结构,用[K]近邻结构差异与点集的变换误差作为匹配的收敛条件,以解决图像目标发生变化而导致的[K]近邻结构不一致及[K]近邻结构相同时仍然存在干扰点两个问题,最终实现快速精确的特征匹配。     

智能短信就业服务平台的设计与实现

通过对短信技术与就业问题的综合研究,提出一种在就业网站依托下,基于本体和Agent技术的短信就业服务解决方案。制定了就业领域本体,提出相容匹配算法,构造了求职、招聘、中介三方Agent模型,实现智能检索和双向推送,并以求职Agent为例描述短信就业平台的实现过程。     

一种基于目标属性特征的多假设关联算法

低时间分辨率遥感成像观测使得合适的目标运动模型难以建立,目标的运动状态变量无法准确估计,造成基于Kalman滤波等运动状态估计算法的经典多目标关联算法不再适用。该文针对该问题提出了一种基于目标属性特征的多假设关联算法,以目标的属性特征作为关联的基本参量,衡量观测到航迹的匹配程度。仿真实验结果证明,该算法对基于低时间分辨率遥感图像的机动目标关联问题具有适用性。     

中介相似性量度的图像匹配

图像匹配是图像信息领域中一个非常重要的技术。以中介真值程度的数值化度量为基础,建立了中介相似性量度,设计了采用中介相似性量度的灰度信息图像匹配算法。实验结果表明,与已有的典型算法处理结果相比较,基于中介相似性量度的匹配算法具有良好的抗噪性和一定的抗失真性,且具有较高的匹配精度和匹配速度。     

基于马尔可夫链的动态多目标快速跟踪

针对目标跟踪过程中常见的碰撞遮挡问题,提出一种视频图像序列的多目标快速跟踪方法。该方法基于卡尔曼算法预测目标位置,采用颜色匹配算法进行前后帧目标的快速匹配,建立马尔可夫链模型并结合目标置信度,判断目标所处的状态,以消除碰撞遮挡现象产生的干扰,实现准确快速的目标跟踪。实验结果表明,该方法能在快速多目标跟踪过程中有效解决目标碰撞、遮挡等问题。     

基于稳定匹配的电子中介匹配研究

介绍了稳定性双边匹配的概念,概括了Gale-Sharply和H-R算法求解1-1和1-k的计算过程.考虑商品的多属性,给出了交易者按综合满意程度对满足自己约束对方的排序计算方法.将Gale-Sharply和H-R算法从理论上扩展到"p-k"情况,用来解决电子中介处理稳定的多对多双边匹配问题.最后证明了扩展算法所得结果的稳定性,并给出了算例.     

面向区域普查的电子侦察卫星任务调度

针对电子侦察卫星区域普查问题(ERSACP)的特点,建立了区域网格空间,提出基于时间、空间、侦察模式匹配的候选侦察活动构造方法;给出了期望侦察效用的概念,建立了问题的多目标规划模型;提出一种嵌入对位学习机制的多目标进化算法(OLMOEA)对其进行求解,同时设计了基于时间可行性判定的初始可行解对位构造算法.仿真实例表明本文模型及算法能够有效解决电子侦察卫星区域普查问题并且性能良好.     

求解VRPTW问题的不确定性目标偏好蚁群算法*

通过分析多目标的、有时间窗的车辆路径问题,对各个目标进行多属性不确定性语言评判,结合相关专家的综合意见以及决策者自身对专家意见的偏好,将决策者对目标属性的离散意见转换为对各目标的综合意见;通过定义一种综合排序指标来确定决策者对各目标的偏好权重,依据目标权重和各目标函数的规范化处理值,构建评价有时间窗的车辆路径问题的多目标偏好的综合适应度函数,将多目标问题转换为单目标问题,进而采用最大—最小蚂蚁系统算法对该问题进行求解;最后通过一个算例来说明该算法的有效性。     

Interactive balance space approach for solving multi-level multi-objective programming problems

This paper studies a multi-level multi-objective decision-making (ML-MODM) problems with linear or non-linear constraints. The objective functions at each level are non-linear functions, which are to be maximized or minimized.This paper presents a three-level multi-objective decision-making (TL-MODM) model and an interactive algorithm for solving such a model. The algorithm simplifies three-level multi-objective decision-making problems by transforming them into separate multi-objective decision making problems at each level, thereby avoiding the difficulty associated with non-convex mathematical programming. Our algorithm is an extension of the work of Shi and Xia [X. Shi, H. Xia, Interactive bi-level multi-objective decision making, Journal of the Operational Research Society 48 (1997) 943-949], which dealt with interactive bi-level multi-objective decision-making problems, with some modifications in assigning satisfactoriness to each objective function in all the levels of the TL-MODM problem. Also, we solve each separate multi-objective decision making problem of the TL-MODM problem by the balance space approach.A new formula is introduced to interconnect the satisfactoriness and the proportions of deviation needed to reflect the relative importance of each objective function. Thus, we have the proportions of deviation including satisfactoriness.In addition, we present new definitions for the satisfactoriness and the preferred solution in view of singular-level multi-objective decision making problems that corresponds to the η-optimal solution of the balance space approach. Also, new definitions for the feasible solution and the preferred solution (η-optimal point) of the TL-MODM problem are presented. An illustrative numerical example is given to demonstrate the algorithm.     

改进GSA算法在协同制造任务分配中的应用

针对网络化协同制造中的任务分配问题,建立了以制造任务完成时间、完成成本、产品工艺质量为目标的多目标优化模型,提出了模型求解的改进遗传模拟退火（Genetic Simulated Annealing,GSA）算法。建立了协同制造任务分配的层次结构模型,应用模糊层次分析法分析了时间、成本和工艺质量等因素在协同制造任务分配过程中的相对重要性。设计了优化模型求解的改进遗传模拟退火算法,并结合具体实例验证了算法的有效性和优越性。     

Multi-objective colonial competitive algorithm for hybrid flowshop problem

This study analyses the multi-objective optimization in hybrid flowshop problem, in which two conflicting objectives, makespan and total weighted tardiness, are considered to be minimized simultaneously. The multi-objective version of Colonial Competitive Algorithm (CCA) for real world optimization problem is introduced and investigated. In contrast to multi-objective problems solved by CCA, presented in the literature, which used the combination of the objectives as single objective, the proposed algorithm is established on Pareto solutions concepts. Another novelty of this paper is estimating the power of each imperialist by a probabilistic criterion for this multi objective algorithm. Besides that, the variable neighborhood search is implemented as an assimilation strategy. Performance of the algorithm is finally compared with a famous algorithm for scheduling problem, NSGA-II, and the multi-objective form of CCA [28].     

基于偏好的多目标遗传算法

多目标优化问题中,人们往往只是对目标空间的某一区域感兴趣,因此这就需要在这一特定的区域能够得到比较稠密的Pareto解,但传统的方法权值法无法满足这种需求而且不能处理目标空间是非凸的情况,遗传算法虽然是现在公认的处理多目标优化问题比较有效的方法,但遗传算法是在目标空间内进行全空间寻优,因此最终得到的Pareto解是均匀分布的,这样遗传算法也不能满足人们的这一要求。针对这个问题提出了基于偏好的多目标遗传算法,把个人偏好加到优化过程中,利用偏好信息来引导优化方向,通过仿真把该算法和权值法、NSGA-II进行比较,结果证明了该算法的可行性和有效性。     

A statistical model-based algorithm for ‘black-box’ multi-objective optimisation

The problem of multi-objective optimisation with ‘expensive’ ‘black-box’ objective functions is considered. An algorithm is proposed that generalises the single objective P-algorithm constructed using the statistical model of multimodal functions and concepts of the theory of rational decisions under uncertainty. Computational examples are included demonstrating that the algorithm proposed possess several expected properties.     

Integrated production and delivery with single machine and multiple vehicles

This paper considers a class of multi-objective production–distribution scheduling problem with a single machine and multiple vehicles. The objective is to minimize the vehicle delivery cost and the total customer waiting time. It is assumed that the manufacturer’s production department has a single machine to process orders. The distribution department has multiple vehicles to deliver multiple orders to multiple customers after the orders have been processed. Since each delivery involves multiple customers, it involves a vehicle routing problem. Most previous research work attempts at tackling this problem focus on single-objective optimization system. This paper builds a multi-objective mathematical model for the problem. Through deep analysis, this paper proposes that for each non-dominated solution in the Pareto solution set, the orders in the same delivery batch are processed contiguously and their processing order is immaterial. Thus we can view the orders in the same delivery batch as a block. The blocks should be processed in ascending order of the values of their average workload. All the analysis results are embedded into a non-dominated genetic algorithm with the elite strategy (PD-NSGA-II). The performance of the algorithm is tested through random data. It is shown that the proposed algorithm can offer high-quality solutions in reasonable time.     

基于模糊偏好的多目标成像卫星调度方法研究

不确定条件下的成像卫星调度问题是一个多目标优化问题。借鉴连续函数的鲁棒性优化思想,提出了一种基于邻域的鲁棒性指标,考虑多种约束条件,建立了多目标成像卫星调度模型。在考虑目标间偏好的情况下,提出了一种基于模糊偏好的多目标遗传算法。实例研究表明,该模型和算法能够有效地解决不确定条件下的成像卫星调度问题。     

一种基于正交视图的三维模型多特征匹配算法

针对现今多数三维检索算法在匹配精度、检索速度以及算法复杂度三者难以相互兼顾的问题,文中提出一种基于正交视图的三维模型多特征匹配算法。首先对被检索三维模型的6个正视角进行投影,获得6个正视图像;接着分别用灰度级图像来描述各个正视图特征,并根据投影后模型各面的分布情况填补顶点与面片之间的间隙;然后动态提取每个灰度级图像的投影直方图特征和Zernike矩特征;最后在分析各特征的优缺点的基础上,融合多个特征来匹配三维模型的相似度。与传统LFD算法和D2算法进行对比实验,结果表明,文中算法能较好地提高对三维模型检索的查全率与查准率,具有计算量小、匹配精度高、运行速度快的优点。