The location selection problem for the household activity pattern problem

In this paper, an integrated destination choice model based on routing and scheduling considerations of daily activities is proposed. Extending the Household Activity Pattern Problem (HAPP), the Location Selection Problem (LSP–HAPP) demonstrates how location choice is made as a simultaneous decision from interactions both with activities having predetermined locations and those with many candidate locations. A dynamic programming algorithm, developed for PDPTW, is adapted to handle a potentially sizable number of candidate locations. It is shown to be efficient for HAPP and LSP–HAPP applications. The algorithm is extended to keep arrival times as functions for mathematical programming formulations of activity-based travel models that often have time variables in the objective.     

Discrete dynamic models for freeway incident detection systems

This paper considers the problem of freeway incident detection within the general framework of computer‐based freeway surveillance and control. A new approach to the detection of freeway traffic incidents is presented based on a discrete‐time stochastic model of the form ARIMA (0, 1, 3) that describes the dynamics of traffic occupancy observations. This approach utilizes real‐time estimates of the variability in traffic occupancies as detection thresholds, thus eliminating the need for threshold calibration and lessening the problem of false‐alarms. Because the moving average parameters of the ARIMA (0, 1, 3) model change over time, these parameters can be updated occasionally. The performance of the developed detection algorithm has been evaluated in terms of detection rate, false‐alarm rate, and average time‐lag to detection, using a total of 1692 minutes of occupancy observations recorded during 50 representative traffic incidents.     

基于KBE技术的复杂零件CAM系统研究

针对复杂零件数控编程工作目前存在的问题,将知识工程（Knowledge Based Engineering,KBE）技术引入复杂零件的数控编程中,系统地阐述了复杂零件广义知识库的内涵及构造原理,通过知识的获取、学习及推理,形成复杂零件的加工工艺决策,并在UG平台上运用二次开发技术,建立了复杂零件的智能数控编程导航模板,构造出基于广义知识库的复杂零件智能数控编程体系．开发的CAM系统经初步应用,证明可行,从而使复杂零件的数控编程过程简单化、高效化、智能化．     

整数规划PSO算法在备件优化配置中的应用研究

备件优化是提高装备可靠度的有效途径,以一般微粒群（PSO）算法为基础,根据备件优化的特点,提出求解整数规划问题的PSO算法。建立费用约束条件下的备件配置的优化模型,并给出了求解方法。结合算例,验证了方法的有效性及实用性。     

公交线路配车问题的不确定双层规划模型

为合理优化公交线路配车,考虑现实中公交站点乘客数量不确定性因素,引入不确定理论构建公交线路配车的不确定双层规划模型. 上层目标为公交运营企业的收益最大化,下层目标为乘客出行时间和费用总成本最小,约束条件是政府要求的服务水平、乘车率,通过 MATLAB进行编程求解. 以南昌市210 路公交为例,利用所构建的不确定双层规划模型对早高峰07:00-08:00 配车进行优化,在给定80%乘车率的约束条件下,单方向配车数量由26 辆减少到23 辆,减少11.5%;优化后高峰小时乘客总加权成本相比优化前小幅增加0.5%,基本持平;高峰小时该线路的利润比优化前增加了112 元,提高29.6%. 结果显示,利用所构建模型优化早高峰小时线路配车效果明显. 该研究为公交运营者考虑现实中不确定因素更合理地优化线路配车提供了理论支持.     

基于Epsilon 约束法的高速铁路客票多目标定价研究

高铁客票定价是多目标定价问题,既要保障旅客福利,又要增加企业合理利润. 以企业利润和旅客福利作为高铁定价目标,考虑旅客差异和不同运距情境下的多种运输方式竞争,研究高铁客票多目标定价. 结合Epsilon约束法构建双层规划模型,根据分层序列思想分解多目标问题,设计松弛算法得到纳什均衡解,由解对应的目标值得到帕累托边界,确定多目标定价最优决策. 计算结果表明,对比量价波动和目标值改进,多目标定价适合票价改革要求,时间敏感型客票和短途客票有较高涨价空间,多种运输方式竞争影响定价实施效果. 将 Epsilon 约束法应用于求解高铁客票定价多目标问题,有利于优化客运企业与旅客利益,为铁路部门提供高铁客票定价思路.     

城市绿色交通规划:建设"和谐交通"社会的必由之路

城市绿色交通是实现健康的、可持续发展的城市交通系统的必由之路。传统的城市交通规划存在着许多弊端．应按绿色交通规划的新理念,创新城市交通规划的思维,规划建设以人为本的和谐交通社会。     

Assessing additional fuel consumption from cabin thermal comfort and auxiliary needs on the worldwide harmonized light vehicles test cycle

Standards for fuel consumption and carbon dioxide emissions are implemented worldwide in most light-duty vehicle markets. Regulatory drive cycles, defined as specific time-speed patterns, are used to measure levels of fuel consumption and emissions. These measurements should realistically reflect real world driving performance, however there is increasing concern about their adequacy due to the discrepancies observed between certified and real world consumption and emissions values. One of the main reasons for the discrepancy is that current testing protocols do not account for non-mechanical vehicle energy needs, such as passengers’ thermal comfort needs and the use of electric auxiliaries on-board. Cabin heating and cooling can especially lead to considerable increase in vehicle energy consumption. This paper presents a simulation-based assessment framework to account for the additional fuel consumption related to the cabin thermal energy and auxiliary needs under the worldwide-harmonized light vehicles test procedure (WLTP). A vehicle cabin model is developed and the thermal comfort energy needs are derived for cooling and heating, depending on ambient external temperature under cold, moderate and warm climates. A modification to the WLTP is proposed by including the generated power profiles for thermal comfort and auxiliary needs. Dynamic programming is used to compute the fuel consumption on the modified WLTP for a rechargeable series hybrid electric vehicle (SHEV) architecture. Results show consumption increases of 20% to 96% compared to the currently adopted WLTP, depending on the considered climate.     

Optimisation and heuristic approaches for assigning inbound containers to outbound carriers

Due to economical and/or geographical constraints, most of the time overseas containers cannot be directly shipped to their destinations. These containers visit transhipment ports where they are first unloaded and temporarily stored and then loaded onto smaller vessels (feeders) to be transported to their final destinations. The assignment of these containers to outbound vessels necessitates several factors to be taken into account simultaneously. In this paper, we develop a mathematical model to reflect multiple objectives with priorities and to assign these containers to different vessels at the transit container port terminal. Although we solve a single-objective (with the weighted sum of objectives) mathematical model to optimality, we also propose two heuristic approaches to solve this complex problem for a transit agency. The first heuristic is shipment based and has four variants differing in how the opportunity costs of the assignments are calculated. The second greedy heuristic is trip based, where the goal is to maximise the capacity utilisation of the vessels. The heuristics return very promising solutions in ignorable computational times. We also provide real-life cases and present our conclusions.