基于支持向量机的物流量预测——以成都市为例

考虑到支持向量机强大的泛化能力,运用支持向量机技术预测了成都市近期和中期物流量.研究表明,随着样本数据的增加,支持向量机的预测值与实际值间的相对误差总体呈下降趋势,并且与多元线性回归方法相比,支持向量机具有较高的预测精度,证明了支持向量机用于物流量预测的有效性.     

层次分析法在泊车诱导中的应用

通过层次分析法分析涉及停车场运营的泊车路径规划、上下层泊位选取、泊车效率、历史泊车时问等因素对？白位经济性的贡献程度,做出各种诱导费用方案并通过线性加权计算。比较结果后做出选择,以达到该类自动化立体停车库的运营成本最低,在路径规划计算上引入Lee算法,进行最短路径求解。     

船舶自动识别系统AIS模拟器的研制与开发

根据AIS模拟器的功能仿真指标,并结合AIS界面仿真、操作程序仿真、危险目标参数的计算及各种显示模式间的转换,对AIS模拟器的研制开发做了阐述.该模拟器较全面地仿真了日本新型FA-150 AIS设备并且满足AIS评估规范的要求.     

Cargo Container Loading Plan Model and Solution Method for International Air Express Carriers

Abstract

In this article, a cargo container loading plan model is developed based on the operations of FedEx, the international air express carrier. The objective is to minimize total container handling cost, subject to related operating constraints. The model is expected to be a useful planning tool whereby international air express carriers such as FedEx can decide on container loading plans that will lead to lower operating costs, thus enhancing profits and market competitiveness. The model is formulated as a non-linear mixed integer program that is characterized as NP-hard. A solution method is then developed, with the use of the mathematical programming solver, CPLEX, to solve the problem efficiently. To evaluate the model and the solution method, we perform a case study using data from FedEx. The preliminary results indicate that the model and the solution method are both efficient and effective.     

Daily newspaper distribution planning with integer programming: an application in Turkey

Abstract

This paper concerns the newspaper distribution problem. It addresses the transportation of newspapers from printing plant to newsagents with distribution vehicles under various particular constraints. The objective is to minimize the distance traveled by the vehicles and/or the number of vehicles. In this study, the routes for vehicles of a leading newspaper distributor company in the Turkish press sector are examined. The problem is defined as determining optimal delivery routes for a fleet of homogeneous vehicles, starting and ending at the printing plant that is required to serve a number of geographically dispersed newsagents with known demands under capacity and time constraints, while minimizing the total distribution cost. An integar linear programming model is proposed as a solution using Cplex. Computational results demonstrate that the proposed model is fast and able to find optimal solutions for problem scenarios with up to 55 newsagents within reasonable computing times. It was found that the proposed model reduced the delivery cost by 21% on average when compared to the current manual method. The results show that this model is adequate for medium-sized distribution problems.     

An adaptive neural network-fuzzy linear regression approach for improved car ownership estimation and forecasting in complex and uncertain environments: the case of Iran

This paper applies a novel adaptive approach consisting of Artificial Neural Network (ANN) and Fuzzy Linear Regression (FLR) to improve car ownership forecasting in complex, ambiguous, and uncertain environments. This integrated approach is applied to forecast car ownership in Iran from 1930 to 2007. In this study, the level of car ownership is viewed as the result of demographic, politico-social, and urban structure factors including average family size, total population density, urban population density, urbanization rate, gross national product per capita, gasoline price, and total road length. To capture the potential complexity, uncertainty, and linearity relation between the car ownership function and its determinants, ANN and FLR (including eight well-known FLR) approaches are applied to the collected data. Next, the preferred ANN is selected based on sensitivity analysis results for the test data while the preferred FLR is identified with regard to ANOVA and MAPE results. The results obtained from the performance comparison demonstrate the considerable superiority of the preferred ANN over the preferred FLR regarding the nonlinear and complex nature of the car ownership function in Iran. This is the first study that presents an ANN-FLR approach for car ownership forecasting capable of handling complexity and non-linearity, uncertainty, pre-processing, and post-processing.     

物资保障网络防卫力量分配的最大覆盖模型

针对后勤防卫中的防卫力量部署问题,根据物资保障网络的结构特点,建立了防卫力量分配的最大覆盖模型.模型表示为双层规划形式,采用保障基地能够覆盖的需求量衡量敌我双方的攻击效果与防护效果.上层规划的目标是最大化己方保护q个保障基地的防护效果,下层规划的目标是最大化敌方攻击r个保障基地的攻击破坏效果.根据模型的特点,采用隐式枚举算法对模型进行了求解.算例应用表明,模型所得分配方案的防护效果优于传统的以网络元素脆弱性为决策依据所得分配方案的防护效果.     

集装箱班轮多港挂靠循环航次舱位分配

舱位分配优化是集装箱班轮经营中的重要决策问题。基于收益管理的原理,利用概率统计方法,计算出在一个多港挂靠循环航次所包括的各个航段应为普通客户预留的舱位数量;建立了包含空箱调运问题的舱位分配随机规划模型;通过确定各航段长期合同客户舱位数量的上下限,将随机规划模型转化为可以求解的确定型规划模型。算例分析显示了该模型及算法的有效性。     

美国高承载率车道拥挤收费方案建模

近年来HOT车道（即高承载率车道拥挤收费方案）已成为美国重要的道路拥挤收费策略.为引鉴其实施经验和管理理论,首先介绍了HOT车道概念与特征,然后采用交通行为建模方法构建了HOT车道管理者与出行者互馈决策的双层规划模型.上层模型模拟管理者的定价策略;下层交通均衡模型模拟个体出行者根据收费水平和交通状态变化而调整出行选择的行为.根据实施方案和应用条件,设计算例分析评价18 种可能情形下HOT车道的拥挤管理效果.结果表明,较传统拥挤管理策略,HOT车道缓堵效果更高;同类出行者假设可能会低估HOT车道的缓堵效果;不同的政策目标下HOT车道的实施效果差异显著.