Multi-objective optimization of a road diet network design

The present study focuses on the development of a model for the optimal design of a road diet plan within a transportation network, and is based on rigorous mathematical models. In most metropolitan areas, there is insufficient road space to dedicate a portion exclusively for cyclists without negatively affecting existing motorists. Thus, it is crucial to find an efficient way to implement a road diet plan that both maximizes the utility for cyclists and minimizes the negative effect on motorists. A network design problem (NDP), which is usually used to find the best option for providing extra road capacity, is adapted here to derive the best solution for limiting road capacity. The resultant NDP for a road diet (NDPRD) takes a bi-level form. The upper-level problem of the NDPRD is established as one of multi-objective optimization. The lower-level problem accommodates user equilibrium (UE) trip assignment with fixed and variable mode-shares. For the fixed mode-share model, the upper-level problem minimizes the total travel time of both cyclists and motorists. For the variable mode-share model, the upper-level problem includes minimization of both the automobile travel share and the average travel time per unit distance for motorists who keep using automobiles after the implementation of a road diet. A multi-objective genetic algorithm (MOGA) is mobilized to solve the proposed problem. The results of a case study, based on a test network, guarantee a robust approximate Pareto optimal front. The possibility that the proposed methodology could be adopted in the design of a road diet plan in a real transportation network is confirmed.     

城市公路客运站选址与班线分配方法研究

以旅客出行的时间消耗降最低为目标,兼顾客运站的建设成本和经营效益,建立公路客运站的选址与班线分配模型。通过遗传算法求解,并请专家对最好的几组计算结果予以评估和修正,得到客运站的最优选址和班线分配方案。     

FWD在旧水泥混凝土路面弯拉弹性模量检测中的应用研究

结合莞深高速公路K0+000～K41+000段改扩建工程勘测设计的实际需要,按我国现行的相关技术规范要求,采用FWD的先进检测手段,对该路段水泥混凝土路面面板的动态弯沉及弯沉盆进行现场测定,在参考国内外研究成果的基础上,建立了弯拉弹性模量反算的数学模型,为旧路大修工程设计提供了路面性能评价依据和设计参数.     

基于遗传算法求解车间设备布局优化问题

车间设备布局问题,是一个NP难问题.许多学者利用启发式算法来求解并取得了一定的成果,但在模型中存在距离定义不合理的情况,均采用绝对距离的方式,存在不符合实际和计算不准确的情况;本文对距离的定义进行了改进,并利用遗传算法对改进后的模型进行求解,效果良好,达到了预期目标.     

基于随机需求的城市公交车辆调度问题的研究

在公交车辆调度问题上,考虑到公交调度中客流需求的不确定因素,引入随机需求调度模型及其相关概念,然后对优化模型进行实例求解,结果证明该模型是可行的。     

基于改进免疫遗传机理的动态路径诱导算法研究

针对传统算法存在的不足,提出基于改进的免疫遗传机理的动态路径诱导算法。通过引入单点交叉算子配合控制策略的改进思想,在宏观上控制交叉过程以及构造优化简单的目标函数,较好地弥补了传统遗传算法早熟收敛、陷入局部最优解、运算效率较低等问题。最后采用此算法进行路网实例计算,结果表明该算法能较大程度地提高路网利用率,减少交通拥堵。     

考虑路段失效的军事物流配送中心选址模型

针对战场保障网络常常遭受敌人打击的现象,建立了考虑路段失效的军事配送中心可靠选址模型.模型为双层规划形式,上层规划的目标是优化系统在无路段失效和出现路段失效时所覆盖的总的需求量,下层规划的目标是最小化某一路段失效时系统覆盖的需求量.采用启发式算法求解下层规划,运用遗传算法求解整个模型.通过一个算例验证模型的优越性和算法的有效性.算例结果表明,尽管模型所得选址方案在无路段失效时覆盖的需求量,小于不考虑路段失效的最大覆盖模型选址方案覆盖的需求量,但在最佳路段失效时模型选址方案的覆盖效果优于后者.     

船舶汽轮机组优化设计研究

汽轮机组是船舶动力装置的重要组成部分,其重量和尺寸是影响船舶动力装置重量体积及布置的重要因素.建立包括汽轮机、冷凝器和齿轮减速器设计三部分的船舶汽轮机组数学模型,以汽轮机组重量最小为目标函数和在给定的约束条件下,采用不同的优化算法对机组进行了优化设计.与原方案相比,采用优化方案后汽轮机组重量明显减小,改进的自适应遗传算法有更好的优化性能,优化效果显著.     

Train rescheduling model with train delay and passenger impatience time in urban subway network

This paper considers the train rescheduling problem with train delay in urban subway network. With the objective of minimizing the negative effect of train delay to passengers, which is quantified with a weighted combination of travel time cost and the cost of giving up the planned trips, train rescheduling model is proposed to jointly synchronize both train delay operation constraints and passenger behavior choices. Space–time network is proposed to describe passenger schedule‐based path choices and obtain the shortest travel times. Impatience time is defined to describe the intolerance of passengers to train delay. By comparing the increased travel time due to train delay with the passenger impatience time, a binary variable is defined to represent whether the passenger will give up their planned trips or not. The proposed train rescheduling model is implemented using genetic algorithm, and the model effectiveness is further examined through numerical experiments of real‐world urban subway train timetabling test. Duration effects of the train delay to the optimization results are analyzed. Copyright © 2017 John Wiley & Sons, Ltd.     

Multi-objective re-synchronizing of bus timetable: Model,complexity and solution

This work is originally motived by the re-planning of a bus network timetable. The existing timetable with even headways for the network is generated using line by line timetabling approach without considering the interactions between lines. Decision-makers (i.e., schedulers) intend to synchronize vehicle timetable of lines at transfer nodes to facilitate passenger transfers while being concerned with the impacts of re-designed timetable on the regularity of existing timetable and the accustomed trip plans of passengers. Regarding this situation, we investigate a multi-objective re-synchronizing of bus timetable (MSBT) problem, which is characterized by headway-sensitive passenger demand, uneven headways, service regularity, flexible synchronization and involvement of existing bus timetable. A multi-objective optimization model for the MSBT is proposed to make a trade-off between the total number of passengers benefited by smooth transfers and the maximal deviation from the departure times of the existing timetable. By clarifying the mathematical properties and solution space of the model, we prove that the MSBT problem is NP-hard, and its Pareto-optimal front is non-convex. Therefore, we design a non-dominated sorting genetic (NSGA-II) based algorithm to solve this problem. Numerical experiments show that the designed algorithm, compared with enumeration method, can generate high-quality Pareto solutions within reasonable times. We also find that the timetable allowing larger flexibility of headways can obtain more and better Pareto-optimal solutions, which can provide decision-makers more choice.