多模式交通条件下合理制定旅客票价的优化模型及算法

在本文中,充分考虑了旅客和交通管理部门两方面的利益,提出了一个双层规划模型来描述城市间多种交通方式竞争条件下合理制定旅客票价问题。在此模型中,既保障了旅客使自己的广义出行费用最小,又使得交通管理部门在客运市场的竞争中取得最大的经济效益。然后给出了求解该模型的基于灵敏度分析的启发式算法 (SAB)。最后用一个实际算例说明了该模型及算法的应用。     

合理制定铁路客票价格的优化模型及算法

在充分考虑出行者和铁路客运部门两方面的利益情况下 ,提出一个双层规划模型以得到在多种交通方式竞争条件下的铁路客票价格制定的最优策略 .既保障了出行者使自己的广义出行费用最小 ,又能使铁路客运部门在运输市场竞争中取得的经济效益最大 .并且给出了求解该模型的 SAB算法。最后用一个简单的算例说明了模型及算法的应用     

O-D需求估计的双层规划模型及基于灵敏度分析的求解算法

本文在考虑三种交通模式 (一般机动车,公交车,自行车)的基础上,建立了一般拥挤网络多模式OD需求估计问题的双层规划模型,给出了一个基于灵敏度分析的启发式求解算法,并进行了数值试验。试验结果表明,本文所给的模型和算法不仅能较好地给出OD需求的估计值,而且同时还给出了各模式路段流量的估计值。     

产品优化设计的用户满意模型

研究品质功能展开的产品优化设计问题. 考虑产品设计过程中的设计预算和非精确性, 引进计划可达水平、实际计划水平等概念,提出产品优化设计的用户满意模型及参数规划求解 方法. 此方法给出满足设计预算的不同可能性条件下的设计方案,供产品设计负责人做出不同 的方案选择,更能反映设计过程的实际情况.     

An Integrated Logistic Model for Predictable Disasters

In the aftermath of a disaster, the relief items are transported from temporary warehouses (Staging Areas, SAs) to the Points of Distribution (PODs). Reducing the response time to provide relief items to disaster victims and cost minimization are two important objectives of this study. We propose an integrated optimization model for simultaneously determining (1) locations of staging areas, (2) inventory assignments to these SAs, (3) selecting sizes and numbers of trucks, and (4) routing of trucks from SAs to PODs. We also introduce another variable, a value function, which forces the model to reduce the logistics response time. We study the interactions among these variables through extensive sensitivity analysis. The time horizon for supply of relief items to disaster areas is usually limited to six days after the disaster occurs. Therefore, we use the proposed optimization model in a rolling‐horizon manner, one day at a time. This reduces daily demand uncertainty. We analyze three disaster scenarios: (1) a low impact disaster, (2) a medium impact disaster, and (3) a high impact disaster. We conduct 720 experiments with different parameter values, and provide answers to the following questions that are useful for the logistic managers: (i) What are the right sizes (in terms of storage capacities) of SAs closer to the PODs? (ii) How should the budget be allocated in a disaster scenario? (iii) What mix of different types (in terms of sizes) of trucks should be selected in a given scenario? The most important managerial insights include: (i) operational budget beyond a limit does not improve the operational efficiency, (ii) when the budget is very low, it is essential to select smaller SAs close to the PODs in order to carry out operations in a feasible manner, (iii) when the impact of disaster is high, it is always beneficial to select larger SAs close to the PODs (as long as the budget is not very low), (iv) when the budget is high and the impact of disaster is not very high, the emergency management administrators need to select SAs prudently based on the tradeoff between the operational cost and the humanitarian value, and (v) the cost of operations is higher when all the trucks are of the same type compared to the case when there is a mix of different types of trucks. Also, we find that the optimal selection of SAs is not impacted by different combinations of the types of trucks. The focus of this study is on disasters that can be forecasted in advance and provide some lead time for preparations, for example, hurricanes. In order to understand the disaster management process of such disasters and develop our model, we (i) interviewed several emergency management administrators, and (ii) studied the disaster management processes available in documents released by various government agencies.     

基于Vague集和属性综合评价的股票投资价值分析方法

对二级市场上同一行业内的不同股票进行投资价值分析是一个系统综合评价问题。本文从评价指标的选择、单项指标的评价、多项指标的综合评价和属性识别准则四部分来阐述属性测度理论在股票投资价值分析中的应用。特别需要指出的是,股票投资价值评价指标体系的建立和指标权重的确定应用了Vague集的理论和方法。最后,我们应用属性综合评价方法对电子元器件制造业的公司股票进行投资价值分析,结果验证了该方法的实用性和正确性。     

公交系统随机平衡网络设计模型及求解算法

本文根据公交网络的具体特点,对公交网络进行了系统的描述,提出一个双层规划模型来描述随机平衡公交网络设计问题。在双层规划模型中,上层模型为一个标准的公交网络设计模型,下层模型是一个公交网络随机平衡配流模型。针对所提出的模型,设计了基于灵敏度分析的求解算法。最后,给出一个简单算例加以证明。     

Sensitivity Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is fraught with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 billion dollars to 3 billion dollars in losses late on the 12th to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm struck the resort areas of Charlotte Harbor and moved across the densely populated central part of the state, with early poststorm estimates in the 28 dollars to 31 billion dollars range, and final estimates converging at 15 billion dollars as the actual intensity at landfall became apparent. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has a great appreciation for the role of computer models in projecting losses from hurricanes. The FCHLPM contracts with a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a sophisticated computer model based on the Holland wind field. Sensitivity analyses presented in this article utilize standardized regression coefficients to quantify the contribution of the computer input variables to the magnitude of the wind speed.     

Fuzzy integrated QFD,FMEA framework for the selection of lean tools in a manufacturing organisation

Lean Manufacturing (LM) is a well-established system to improve performance of any manufacturing industry by eliminating wastes through globally accepted tools and techniques. Industries are trying to adapt lean principles in order to optimise the resources like people, equipment, material and schedule for being efficient in the competitive market. This paper proposes an integrated approach for selecting appropriate lean tools in reliable lean perspective to enhance these critical resources. The approach exercise a hybrid model which uses fuzzy QFD to prioritise the critical resources in relation with identified wastes and fuzzy FMEA to assess the risk associated with each sub elements to address lean implementation. For waste identification, plant layout and Value Stream Mapping are considered. The model is demonstrated based on the data collected from a manufacturing industry to illustrate the application. Significant improvements are quantified with the help of future state map and plant layout.     

Uncertainty Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 to 3 billion dollars in losses late on August 12 to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the 28 to 31 billion dollars range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables.