基于多目标优化遗传算法的武器-目标分配

针对武器‐目标火力分配问题,建立了基于效能最大和用弹量最少的多目标优化模型。基于 Pareto集非劣分层思想对遗传算法进行改进,利用非劣分层遗传算法处理武器‐目标分配多目标优化问题。非劣分层遗传算法通过对种群内的所有个体的多个目标函数进行非劣分层排序来度量个体的适应能力,通过遗传算法实现多样性进化操作,能够获取Pareto最优解集,以供决策者参考。仿真试验表明：该方法能够获得满意的分配结果,方便快捷地解决多平台多类型武器‐目标分配问题。     

公路运输企业员工激励约束机制研究

在论证公路运输企业建立规范的员工激励约束机制的必要性的基础上,分析了目前公路运输企业员工激励约束机制方面存在的问题。结合对竞争性公路运输企业员工所着重的激励因素问卷调查,提出应以人力资源价值链管理理论为指导,在激励制度设计中融合约束,全面建设“三体系”和“一配套”工程,即岗位职级激励约束体系、全面绩效管理激励约束体系、薪酬激励约束体系和非薪酬配套机制,从而构建完整而有效的公路运输企业员工激励约束机制。     

高速公路路面养护管理排序的一种方法

提出了高速公路路面养护管理的问题,在多目标决策问题研究的基础上,将“加权偏差平方和最小”的群排序方法应用于高速公路路面养护管理的排序问题,并以四川省高速公路的实例进行了案例分析,其目标是为高速公路主管部门和养护部门提供科学有效的决策支持。     

搜索引擎排序算法的探索

搜索引擎是一项崭新而且流行的技术,而检索排序技术是信息检索系统处理结果的核心技术.排序算法的好坏,直接决定搜索引擘效率的高低.文中详细分析了目前流行的3种排序算法:PageRank算法,HillTop算法,竞价算法.介绍各自原理,优缺点以及改进措施,并以PageRank方法为例,详细描述PR值的求解过程.     

物流运输网络模糊最短路径的偏好解

考虑到物流运输网络中存在的不确定性,针对弧长为模糊数的最短路问题,提出了基于加权函数重心法的模糊数排序方法,根据标号法得到网络中从某一指定节点到其他节点的与偏好信息相一致的最短路。该排序方法提供了决策偏好信息的参数化表示,决策者通过设定极大熵加权函数表示的悲观或乐观水平,就可以得到与目前偏好结构相一致的模糊数排序结果,以及相应的模糊最短路权值和选择方案。计算结果显示,在不同的偏好参数下,决策者得到的最短路方案是不同的,而且计算结果与设定的偏好完全一致。     

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创新性地考虑了多车型车辆路径问题中不同车型具有不同的边际费用和行驶费用的问题,并同时考虑车型与任务的相容性,对带时间窗约束的多车型多费用非满载车辆路径问题,以最小化总费用为目标建立了数学模型。由于该模型的NP-hard性质,基于高费用车型的边际费用和单位行驶费用比低费用车型的相应费用都要高以及低费用车型的边际费用远大于高费用车型的单位行驶费用的思想,对该模型设计了一个启发式算法。     

Road pricing—some of the more neglected theoretical and policy implications

The intention of this paper has been to raise some doubts about the extent to which the control of congestion is understood, not as an engineering problem, but as a socio‐economic one concerned with making the most appropriate use of scarce resources.

Despite some doubts, it seems that the basic theory, as applied to a highly simplified situation, is technically correct. What is much less clear, however, is the extent to which the acceptance of this analysis as a basis for policy making in the real world is justified. Even if, qualitatively, its implications are correct, there are significant quantitative uncertainties. Given that governments, local and national, are still pouring considerable sums of money, both through subsidies and investment, into the relief of congestion, it is desirable to change this state of affairs. There seems to be ample scope for the transport economist, the transport planner and the transport engineer to contribute to a debate which has a long and, in places, distinguished pedigree, but where the outcome is as yet considerably outstripped by the importance and complexity of the problems which must be solved.

     

Research on the fully fuzzy time-cost trade-off based on genetic algorithms

It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms （GAs）. In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling.     

Application of Classical Transportation Methods for Solving Fuzzy Transportation Problems

There are several methods, in the literature, for finding a fuzzy optimal solution to fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this study, the shortcomings of some existing methods are pointed out, and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find a fuzzy optimal solution to fuzzy transportation problems with a new representation of trapezoidal fuzzy numbers. The advantages of the proposed methods over existing methods are discussed. Also, it is shown that it is better to use the proposed representation of trapezoidal fuzzy numbers instead of the existing representation of trapezoidal fuzzy numbers for finding a fuzzy optimal solution to fuzzy transportation problems. To illustrate the proposed methods, a fuzzy transportation problem (FTP) is solved using the proposed methods and the obtained results are discussed. The proposed methods are easy to understand and to apply for finding a fuzzy optimal solution to fuzzy transportation problems occurring in real-life situations.     

常规公交运行舒适度的影响因素分析

运行舒适度是衡量常规公交服务质量的重要指标。采用问卷调查形式,从乘客感知的视角,结合重要性因素排序、5级李克特量表与乘客满意度,通过排序分析和SPSS多元线性回归,得到不同承载率时,常规公交运行舒适度的主要影响因素及相应权值。研究表明:承载率L>1时,拥挤、平稳性和卫生是运行舒适度的最主要影响因素,权值分别为0.41,0.33和0.26;承载率L≤1时,卫生、车内噪音和行车平稳性是运行舒适度的评价指标,权值分别为0.38,0.36和0.26。