不确定阻断情景下的路网保护策略研究

当应急服务设施位置确定时,其应急出救效率主要取决于该区域的交通网络条件。在灾前防御阶段对路网采取实施一定的保护措施可以减少因灾害造成的损失。结合可能受灾害造成阻断的道路所需保护成本、阻断后的修复成本以及区域应急出救效率,在考虑道路阻断情景不确定性基础上建立鲁棒优化模型以确定路网保护策略,其中每种道路保护策略所面临的最坏情景被用于衡量该策略的优劣。通过分析模型的特点设计了嵌入Warshall-Floyd算法的模拟退火算法,最后的数值试验显示了算法的有效性并对保护策略和观望策略的性能进行了对比分析。     

一个供需不确定性下的多模式非线性互补分配模型

交通需求和供给不确定是现实交通网络中常见的现象.提出一个供需不确定条件下非对称影响的多模式交通分配模型.提出的模型以条件概率的形式生成不同供需变动情景下的交通流模式,构成一个非线性互补模型,模型中获得的交通流模式,可以用来估计交通网络失效的损失指标和交通网络可靠性衡量指标,不同风险态度的出行者可借助指标来选择可靠性高的路段或避开效率损失高路段.使用一个算例来表明提出模型的适用性和有效性.结果表明,提出的模型能更好的反映不确定性条件下的多种模式交通流演变情况,反映不同的供需变动情景以及不同的出行模式对均衡流模式的影响,进而提高交通网络中用户的出行可靠度.     

考虑禁左条件的用户均衡交通配流模型与算法

交叉口处左转车流是对车流量影响较大的一个流向,也是造成城市交通拥挤和交通事故的关键因素之一,所以越来越多的城市路网选择在交叉口禁止左转来保障主干路车流通畅.在禁左的情况下,出行者究竟如何选择出行路径,究竟应该在哪些交叉口采取禁左管理可以使网络总旅行时间最小?针对以上两个问题,将根据用户均衡(UE)原理,建立考虑交叉口禁左条件的交通配流双层规划模型.利用Frank-Wolfe算法,对下层模型中的出行车辆进行配流,并返回到上层模型计算网络总旅行时间,通过遗传算法确定设置禁左交叉口位置,使得网络总旅行时间达到最小.根据数值算例,展现合理设置禁左交叉口的位置,可以使得交通网络总费用减小.     

基于鲁棒优化的随机时变网络最优路径研究

交通事故、恶劣天气以及偶发的交通拥堵等都会导致道路交通网络中行程时间的不确定性,极大地影响了道路交通系统的可靠性,同时给日常生活中出行计划的制定以及出行路径的选择带来了不便。因此,本次研究将综合考虑道路交通网络中由于交通流量的全天变化所导致的路径行程时间的时变特征,以及由于事故、天气等不确定因素所导致的路径行程时间的随机特征,并以此作为路网环境的假设条件,对出行路径选择问题进行研究。具体地,首先建立行程时间的动态随机变量,并在此基础上模拟构建了随机时变网络。随后,定义了该网络环境下路径选择过程中所考虑的成本费用,并通过鲁棒优化的方法,将成本费用鲁棒性最强的路径视为最优路径。随后,在随机一致性条件下,通过数学推导证明了该模型可以简化为解决一个确定性时变网络中的最短路径问题。最终,具有多项式时间计算复杂度的改进Dijkstra算法被应用到模型的求解中,并通过小型算例验证模型及算法的有效性。结果表明,本研究中所提出的方法可以被高效率算法所求解,并且不依赖于先验行程时间概率分布的获取,因此对后续的大规模实际城市道路网络应用提供了良好的理论基础。此外,由于具有行程时间随机时变特征的交通网络更接近实际道路情况,因此本次研究的研究成果具有较高的实际意义和应用价值。     

关于可靠性设施布局问题的近似算法

设施布局问题的研究始于20世纪60年代,主要研究选择修建设施的位置和数量,以及与需要得到服务的城市之间的分配关系,使得设施的修建费用和设施与城市之间的连接费用之和达到最小.现实生活中, 受自然灾害、工人罢工、恐怖袭击等因素的影响,修建的设施可能会出现故障, 故连接到它的城市无法得到供应,这就直接影响到了整个系统的可靠性.针对如何以相对较小的代价换取设施布局可靠性的提升,研究人员提出了可靠性设施布局问题.参考经典设施布局问题的贪婪算法、原始对偶算法和容错性问题中分阶段分层次处理的思想,设计了可靠性设施布局问题的一个组合算法.该算法不仅在理论上具有很好的常数近似度,而且还具有运算复杂性低的优点.这对于之前的可靠性设施布局问题只有数值实验算法, 是一个很大的进步.     

双模式交通网络中的ATIS信息定价研究

先进的出行者信息系统(ATIS)是一种服务商品,已有的研究多从提高市场占有率的角度对单模式交通网络中的ATIS进行信息定价。多模式交通网络中影响ATIS市场占有率的因素众多,而且ATIS的提供成本往往与信息质量和使用规模同时相关。因此,信息定价问题应从ATIS服务提供商利润最大化的角度进行研究。本文把ATIS信息的单次使用费用和ATIS的信息质量同时作为决策变量,将双模式路网中ATIS的定价问题描述为一个双层规划模型。其中,混合用户均衡模型为下层模型,收益模型为上层模型。然后,基于上海市虹口区的路网数据,对下层模型进行了数值分析,并讨论了相关经济效益问题。此外,本文提出了求解下层模型的MSAF算法,并进一步嵌套了粒子群(PSO)算法,最终得到ATIS服务提供商的最优ATIS信息定价和信息质量提供方案。     

不确定条件下环境友好型资源分配二层规划模型

本文讨论了不确定条件下环境友好型的资源分配问题:其中总公司作为上层领导者在各下属工厂间合理分配资源,以期获得最大收益的同时降低对环境的污染程度;而作为下层从属者的各工厂决定各自产量以期获得最大利润。该问题中的产品价格、生产成本、资源成本等被考虑为随机变量,环境污染指数被考虑为模糊变量,因而本文构造了不确定条件下的机会约束二层资源分配模型。运用等价定理对模型进行转换,并采用交互式满意度法将二层模型转化为单层模型以便求解。最后通过数值算例证实了模型和算法的可行性与有效性。此外,由于模型含有影响模型解的参数,故基于满意度和置信水平分别进行了灵敏度分析,进一步验证了所提出模型的科学性。     

提前期不确定条件下的预防性维修备件存储模型研究

在考虑预防性维修周期和提前期不确定的条件下,分别研究备件存储与其相关的维修费用、缺货费用、库存费用以及订购费用等四种费用之间的关系,明确了备件存储量对各项费用的影响.以各项费用总和最小化为目标,构建了提前期不确定条件下的预防性维修备件存储模型.通过备件存储模型的构建,对备件存储过程中的各项成本进行分析,以期对备件库存策略的确定给出一种解决方案.     

突发事件对交通网络的影响评估指标和方法

近年来,由于自然灾害,不断地环境恶化以及不可预测的灾害侵袭,突发事件时有发生,突发事件可能对交通网络产生非常严重的影响。本文给出了一些指标来表征突发事件对交通网络的影响程度。这些指标适用于用户最优、系统最优以及效率损失等情形。 我们给出了这些指标的性质并讨论了在用户最优、系统最优以及效率损失等情形下的指标之间的关系。交通网络的数值算例表明了关于突发事件的指标的合理性。突发事件对交通网络的影响程度评估对于道路规划、道路维护以及网络脆弱性分析均有重要意义。     

求解用户平衡与系统最优模型的新算法

近些年,国内外许多学者针对交通规划提出了诸如用户平衡(UE)、系统最优(SO)等模型,但由于交通网络的复杂性,这些模型的求解相对困难,考虑到在一般的UE、S0模型中,其约束条件为线性约束与非负约束,给出一种求解交通规划模型的新算法,算法不需使用任何线搜索,只要通过求解一个简单的二次规划问题得到下降方向即可,最后,将该算法应用到简单的交通网络中,并通过与相继平均法(MSA)进行比较,验证了该算法的收敛速度较快。     

Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: A case study of Tehran

In this paper, dynamic dairy facility location and supply chain planning are studied through minimizing the costs of facility location, traffic congestion and transportation of raw/processed milk and dairy products under demand uncertainty. The proposed model dynamically incorporates possible changes in transportation network, facility investment costs, monetary value of time and changes in production process. In addition, the time variation and the demand uncertainty for dairy products in each period of the planning horizon is taken into account to determine the optimal facility location and the optimal production volumes. Computational results are presented for the model on a number of test problems. Also, an empirical case study is conducted in order to investigate the dynamic effects of traffic congestion and demand uncertainty on facility location design and total system costs.     

Integrating link-based discrete credit charging scheme into discrete network design problem

In this paper, we present an optimization model for integrating link-based discrete credit charging scheme into the discrete network design problem, to improve the transport performance from the perspectives of both transport network planning and travel demand management. The proposed model is a mixed-integer nonlinear bilevel programming problem, which includes an upper level problem for the transport authority and a lower level problem for the network users. The lower level sub-model is the traffic network user equilibrium (UE) formulation for a given network design strategy determined by the upper level problem. The network user at the lower level tries to minimize his/her own generalized travel cost (including both the travel time and the value of the credit charged for using the link) by choosing his/her route. While the transport authority at the upper level tries to find the optimal number of lanes and credit charging level with their locations to minimize the total system travel time (or maximize the transportation system performance). A genetic algorithm is used to solve the proposed mixed-integer nonlinear bilevel programming problem. Numerical experiments show the efficiency of the proposed model for traffic congestion mitigation, reveal that interaction effects across the tradable credit scheme and the discrete network design problem which amplify their individual effects. Moreover, the integrated model can achieve better performance than the sequential decision problems.     

Sensitivity Analysis Based Method for Optimal Road Network Pricing

Road pricing is an important economic measure for optimal management of transportation networks. The optimization objectives can be the total travel time or total cost incurred by all the travelers, or some other environmental objective such as minimum emission of dioxide, an so on. Suppose a certain toll is posed on some link on the network, this will give an impact on flows over the whole network and brings about a new equilibrium state. An equilibrium state is a state of traffic network at which no traveler could decrease the perceived travel cost by unilaterally changing the route. The aim of the toll setting is to achieve such an equilibrium state that a certain objective function is optimized. The problem can be formulated as a mathematical program with equilibrium constraints (MPEC). A key step for solving such a MPEC problem is the sensitivity analysis of traffic flows with respect to the change of link characteristics such as the toll prices. In this paper a sensitivity analysis based method is proposed for solving optimal road pricing problems.     

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches.     

A combined facility location and network design problem with multi-type of capacitated links

This article presents a mixed-integer model to optimize the location of facilities and the underlying transportation network at the same time to minimize the total transportation and operating costs. In this problem, it is assumed that for connecting two nodes, there are several types of links in which their capacity, transportation and construction costs are different. The developed model has various applications in telecommunication, emergency, regional planning, pipeline network, energy management, distribution, to just name a few. To solve the model effectively, this paper also proposes a fix-and-optimize heuristic based on the evolutionary fire-fly algorithm. Finally, to validate the model and evaluate the algorithm’s performance, a series of test instances with up to 100 nodes and 600 candidate links with three different levels of quality are reported.     

Solving the robust two-stage capacitated facility location problem with uncertain transportation costs

In this study, we start from a multi-source variant of the two-stage capacitated facility location problem (TSCFLP) and propose a robust optimization model of the problem that involves the uncertainty of transportation costs. Since large dimensions of the robust TSCFLP could not be solved to optimality, we design a memetic algorithm (MA), which represents a combination of an evolutionary algorithm (EA) and a modified simulated annealing heuristic (SA) that uses a short-term memory of undesirable moves from previous iterations. A set of computational experiments is conducted to examine the impact of different protection levels on the deviation of the objective function value. We also investigate the impact of variations of transportation costs that may occur on both transhipment stages on the total cost for a fixed protection level. The obtained results may help in identifying a sustainable and efficient strategy for designing a two stage capacitated transportation network with uncertain transportation costs, and may be applicable in the design and management of similar transportation networks.     

Sensitivity analysis for the asymmetric network equilibrium problem

We consider the asymmetric continuous traffic equilibrium network model with fixed demands where the travel cost on each link of the transportation network may depend on the flow on this as well as other links of the network and we perform stability and sensitivity analysis. Assuming that the travel cost functions are monotone we first show that the traffic equlibrium pattern depends continuously upon the assigned travel demands and travel cost functions. We then focus on the delicate question of predicting the direction of the change in the traffic pattern and the incurred travel costs resulting from changes in the travel cost functions and travel demands and attempt to elucidate certain counter intuitive phenomena such as ‘Braess' paradox’. Our analysis depends crucially on the fact that the governing equilibrium conditions can be formulated as a variational inequality. This work was supported by the Program of University Research, U.S. Department of Transportation (Project number DTRS 5680-C-00007).     

基于离散与连续选址相结合的平面选址问题研究——以华北石油局大牛地气田污水处理厂选址为例

选址问题的研究中,大多考虑的是理论距离(例如欧式距离等);但在实际问题中,真实的公路运输距离和理论距离有较大差异,并且修建公路的成本较高.在尽量利用当前的公路交通网络同时,又能得到最优选址,在现实中具有重要意义.以华北石油局大牛地气田第一采气厂污水处理厂选址为例,分别采用重心法选址、最大值最小化选址、多目标选址等选址的方法得到污水处理厂的备选点,并结合实际距离模拟出了各个备选点的运输费用,再综合考虑当地政策和交通状况等因素,最终得到了使得运输费用最低的新的污水处理厂的位置坐标P(9.33,11.79),在该位置建立污水处理厂比之前的运输方案每年大约可节约511万元的运输费用.方法最大的优点是减小了在选址过程中理论距离与实际距离的误差,在现实中具有一定的指导意义.     

Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model

A good traffic assignment model can be a powerful tool to describe the characteristics of traffic behavior in a road network. The traffic assignment results often play an important role in transportation planning, e.g., an optimal and economical network design. Many traditional traffic assignment models rely heavily on the travel cost function established by Wardrop’s principles; however, the Wardrop’s travel cost function has been proven to be weak for explaining the uncertainty and interactivity of traffic among links. This study tries to construct a traffic assignment model that is different from Wardrop’s in many aspects. First, it considers the cross-effect among the links. Second, a fuzzy travel cost function is established based on the possibility concept instead of precise calculation of traffic volumes. Third, the techniques of fuzzy measure and fuzzy integral are applied to calculate the subjectively perceived travel costs during traffic assignment. Furthermore, in order to validate our model, a detailed network with 22 nodes and 36 links is used to illustrate it. Study results show that our model explains more interactivity and uncertainty of traffic among links when compared with the traditional model of Wardrop’s.