A Model for Evaluation of Transport Policies in Multimodal Networks with Road and Parking Capacity Constraints

This paper presents a model for evaluation of transport policies in multimodal networks with road and parking capacity constraints. The proposed model simultaneously considers choices of travelers on route, parking location and mode between auto and transit. In the proposed model, it is assumed that auto drivers make a simultaneous route and parking location choice in a user equilibrium manner, and the modal split between auto and transit follows a multinomial logit formulation. A mathematical programming model with capacity constraints on road link and parking facilities is proposed that generates optimality conditions equivalent to the requirements for multimodal network equilibrium. An augmented Lagrangian dual algorithm embedded by partial linearization approach is developed to solve the proposed model. Numerical results on two example networks are presented to illustrate the proposed methodology. The results show that the service level of transit, parking charges, road link and parking capacities, and addition of a new parking location may bring significant impacts on travelers’ behavior and network performance. In addition, transport policies may result in paradoxical phenomenon.     

双模式网络停车限制交通需求管理模型与方法研究

在轨道网和公路网并存的双模式交通网络, 合理设计出行终点的停车容量可优化汽车出行需求, 改善路网交通环境。本文通过分析私家车与城市轨道两种交通模式的出行需求, 并考虑私家车模式的终点停车收费服务, 建立了一种带路段环境容量和终点停车需求容量共同约束的交通需求管理模型。模型中路网使用者的出行模式采用二元Logit模型来计算, 而私家车的路线选择行为服从Logit随机用户均衡, 因此该模型是一个带不动点约束的数学规划问题。针对模型求解困难, 文中采用灵敏度分析来获取各路段流量和需求量关于终点容量波动的梯度信息, 进而设计了一种新的灵敏度分析求解算法.最后通过数值仿真实验, 验证了算法的有效性, 同时分析了不同停车收费参数对模型各指标变化趋势的影响。     

Development of a new approach for deterministic supply chain network design

This paper proposes a mixed integer linear programming model and solution algorithm for solving supply chain network design problems in deterministic, multi-commodity, single-period contexts. The strategic level of supply chain planning and tactical level planning of supply chain are aggregated to propose an integrated model. The model integrates location and capacity choices for suppliers, plants and warehouses selection, product range assignment and production flows. The open-or-close decisions for the facilities are binary decision variables and the production and transportation flow decisions are continuous decision variables. Consequently, this problem is a binary mixed integer linear programming problem. In this paper, a modified version of Benders’ decomposition is proposed to solve the model. The most difficulty associated with the Benders’ decomposition is the solution of master problem, as in many real-life problems the model will be NP-hard and very time consuming. In the proposed procedure, the master problem will be developed using the surrogate constraints. We show that the main constraints of the master problem can be replaced by the strongest surrogate constraint. The generated problem with the strongest surrogate constraint is a valid relaxation of the main problem. Furthermore, a near-optimal initial solution is generated for a reduction in the number of iterations.     

区间数型多目标联运路线优化问题的模型与算法

联运路线优化问题直接关系到货物运输的费用、时间和运输质量.首先分析了联运路线优化问题的数学模型及虚拟运输网络图;其次,将区间数排序的思想及属性值为区间数的多属性决策方法引入适应度函数的设计中,提出了一种求解区间数型联合运输路线优化问题的混合型遗传算法,给出了染色体编码、遗传算子设计、适应度函数定义及群体多样性控制的方法;最后用示例对算法的有效性进行了验证.     

碳排放限制下的冷藏集装箱多式联运路径优化

为了降低碳排放限制下的冷藏集装箱多式联运成本,实现节能减排的目的,高效的路径选择至关重要.该文基于碳排放限制的视角,针对多式联运网络中铁路和水路运输具有发班时间限制,以及冷藏集装箱需要考虑制冷费用、货损货差的特点,建立了在碳排放限制下以总成本最低为目标的优化模型.构建总成本时不仅考虑了运输费用和转运费用,还考虑了受发班时间影响而动态变化的冷藏费用和货损费用.设计了遗传算法求解,并进行了算例分析.结果表明:通过该模型和算法,可根据决策者的要求快速地选出成本最少的运输方案,为决策者提供决策支持.     

交通网络建设序列的动态规划方法

交通网络建设序列优化是交通规划中一个重要问题。文章对交通网络设计及其建设序列问题的研究现状进行了分析。按照网络建设中规划者和用户间的关系,以交通网络建设序列下的各阶段系统总费用作为上层规划,以各阶段的交通流用户平衡模型作为下层规划,建立了双层规划模型。并依照问题的特点,采用动态规划的求解方法进行探讨,而下层模型则采用了基于路径搜索的GP算法进行求解。并针对网络规划算例进行了计算,针对固定和变动客流OD两种情况下的结果进行了分析。计算的结果表明,问题的双层规划模型和动态规划求解算法能够为路网规划决策提供支持。     

Weber problems with mixed distances and regional demand

We consider a location problem where the distribution of the existing facilities is described by a probability distribution and the transportation cost is given by a combination of transportation cost in a network and continuous distance. The motivation is that in many cases transportation cost is partly given by the cost of travel in a transportation network whereas the access to the network and the travel from the exit of the network to the new facility is given by a continuous distance.      

多目的地多停车场系统动态停车分配模型

在一个多目的地多停车场系统中,每个目的地附近有多个停车场可供选择,每个停车场也可供多个目的地的停车需求停车。每个目的地的停车需求在各停车场的停车量即为停车分配问题. 本文定义了停车量分配均衡原则:各目的地的驾驶员总是首选最低费用(包括在停车场内的停车费用以及停车时间、步行时间转换后的货币成本,其中停车费用及在停车场内的车位找寻时间都正相关于该停车场当前时刻停车饱和度)的停车场停车;由于停车场具有容量限制,当费用最低的停车场已满则再选择费用次低的停车场,以此类推;所有没被使用的停车场或者比被使用的停车场具有更高的费用或者停车位已满。考虑停车需求和各停车场内空余泊位数的实时动态特性,提出了与该均衡原则等价的数学规划模型,证明了其解的唯一性并设计了求解算法。通过两个算例对模型进行了验证,并再现了目的地附近各停车场内车位占用变化规律,从而为动态停车收费、停车选址规划等提供依据。     

基于正交试验的乘用车运输网络优化方法

在交通部治理公路超限运输的背景下,本文研究了乘用车物流企业多式联运模式下的网络优化问题,以运输网络总成本最小为目标,考虑物流时效、枢纽节点容量及规模经济效应等因素,构建了基于轴辐式理论的运输网络优化模型,提出了混合智能优化算法。针对多参数多水平的寻优问题,对模型的三个关键输入参数,即枢纽节点数量、枢纽节点容量和规模效应折扣系数,引入正交试验方法,降低求解多参数多水平寻优问题的工作量,为确定各参数合理取值提供了新的途径。研究结果表明:枢纽节点容量、折扣系数与枢纽数量三个输入参数对优化结果的影响具有主次顺序,影响程度依次减弱,而且只有枢纽节点容量与折扣系数对乘用车运输网络总效益的影响起显著作用。采用混合轴辐式的网络结构与多式联运的运输组织模式进行优化后的运输网络,相对于原有“点对点”公路运输网络总成本减少10%,从运营管理与成本控制两方面均可有效应对公路治超带来的风险。     

Joint optimization of budget allocation and maintenance planning of multi-facility transportation infrastructure systems

Transportation infrastructure, such as pavements and bridges, is critical to a nation’s economy. However, a large number of transportation infrastructure is underperforming and structurally deficient and must be repaired or reconstructed. Maintenance of deteriorating transportation infrastructure often requires multiple types/levels of actions with complex effects. Maintenance management becomes more intriguing when considering facilities at the network level, which represents more challenges on modeling interdependencies among various facilities. This research considers an integrated budget allocation and preventive maintenance optimization problem for multi-facility deteriorating transportation infrastructure systems. We first develop a general integer programming formulation for this problem. In order to solve large-scale problems, we reformulate the problem and decompose it into multiple Markov decision process models. A priority-based two-stage method is developed to find optimal maintenance decisions. Computational studies are conducted to evaluate the performance of the proposed algorithms. Our results show that the proposed algorithms are efficient and effective in finding satisfactory maintenance decisions for multi-facility systems. We also investigate the properties of the optimal maintenance decisions and make several important observations, which provide helpful decision guidance for real-world problems.     

The plant location problem with demand-dependent setup costs and centralized allocation

Suppose that customers are situated at the nodes of a transportation network, and a service company plans to locate a number of facilities that will serve the customers. The objective is to minimize the sum of the total setup cost and the total transportation cost. The setup cost of a facility is demand-dependent, that is, it depends on the number of customers that are served by the facility. Centralized allocation of customers to facilities is assumed, that is, the service company makes a decision about allocation of customers to facilities. In the case of a general network, the model can be formulated as a mixed integer programming problem. For the case of a tree network, we develop a polynomial-time dynamic programming algorithm.     

After-sales services network design of a household appliances manufacturer

After-sales services have become high-margin businesses that account for larger portions of corporate profits. Delivering the after-sales services is challenging as after-sales services supply chains are significantly different than production–distribution supply chains. The literature provides little guidance on the use of quantitative methods for after-sales services network design. We present a mixed integer linear programming problem formulation to determine warehouse locations, assign repair vendors to facilities and choose mode of transportation while minimizing the total network cost. We transform the large-scale real-life problem of a household appliances manufacturer into a smaller scale to solve optimally in reasonable time. Through a scenario-based approach, we evaluate different configurations of a decentralized network with choices of transportation mode. We test the sensitivity of the solutions. The total cost decreases with additional choices of transportation mode and only slightly increases with the next-day delivery policy while the network solution may change significantly.     

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.     

A primal–dual algorithm for the economic lot-sizing problem with multi-mode replenishment

The classical economic lot-sizing problem assumes that a single supplier and a single transportation mode are used to replenish the inventory. This paper studies an extension of this problem where several suppliers and transportation modes are available. The decision-making process in this case involves identifying (i) the timing for an order; (ii) the choice of shipment modes; and (iii) the order size for each mode. The problem is defined as a network flow problem with multiple setups cost function and additional side constraints. This study provides an MIP formulation for the problem. We also provide an additional formulation of the problem by redefining its decision variables and show that the dual of the corresponding LP-relaxation has a special structure. We take advantage of the structure of the dual problem to develop a primal–dual algorithm that generates tight lower and upper bounds. Computational results demonstrate the effectiveness of the algorithm.     

Object modeling and path computation for multimodal travel systems

This paper describes a multimodal travel system (MTS) designed to address the needs of a variety of demand-responsive transport. An origin–destination (O–D) trip in transportation network can be accomplished by using multiple modes. In urban network passengers may boarding buses or metros to go from one place to another, and modes as autobus or trains are used by passengers to travel between cities. The work focuses on the network object modeling and multimodal shortest path algorithm. A solution to the problem of long-run planning of transit on multimodal network has been implemented and tested. The work presents the general results found, and the proposed algorithm recognizes the set of constraints related to the time schedule and the sequence of used modes in a O–D trip. The aim is to provide a tool for detecting the facilities of using different travel modes through a transportation network. Routings may include distinct combination of rail, and route. Geographic Information Systems (GIS) were invaluable in the cost-effective construction and maintenance of this work and the subsequent validation of mode sequences and paths selections. Attention is devoted to the multimodal path operator as well as to the use of GIS-transit planning.     

0-1 reformulations of the multicommodity capacitated network design problem

We study 0-1 reformulations of the multicommodity capacitated network design problem, which is usually modeled with general integer variables to represent design decisions on the number of facilities to install on each arc of the network. The reformulations are based on the multiple choice model, a generic approach to represent piecewise linear costs using 0-1 variables. This model is improved by the addition of extended linking inequalities, derived from variable disaggregation techniques. We show that these extended linking inequalities for the 0-1 model are equivalent to the residual capacity inequalities, a class of valid inequalities derived for the model with general integer variables. In this paper, we compare two cutting-plane algorithms to compute the same lower bound on the optimal value of the problem: one based on the generation of residual capacity inequalities within the model with general integer variables, and the other based on the addition of extended linking inequalities to the 0-1 reformulation. To further improve the computational results of the latter approach, we develop a column-and-row generation approach; the resulting algorithm is shown to be competitive with the approach relying on residual capacity inequalities.     

考虑订单合并和货物转运的多式联运路径优化研究

为了获得运输的规模经济效应,本文研究了一种考虑订单合并和货物转运的零担多式联运路径优化问题。首先,以总运输成本为目标函数,以网络中的运输工具容量、可以提供的运输工具最大数量、运输工具服务的关闭时间以及订单时间窗为约束,构建混合整数规划模型,在模型中允许多个订单进行合并运输并考虑运输过程中的转运成本。其次,由于多式联运路径优化问题是典型的NP-hard问题,为了快速求解该模型,开发了一种可以快速为该问题提供近似最优解和下界的列生成启发式算法。最后,生成并测试了大量算例,结果表明所开发的列生成启发式算法可以在较短的时间内提供高质量的近似最优解。文章所构建的模型和开发的列生成启发式算法可以为零担自营多式联运物流企业提供高效的决策支持。     

考虑应急设施中断风险与防御的可靠性选址模型研究

为提高应急设施运行的可靠性和抵御中断风险的能力, 研究中断情境下的应急设施选址-分配决策问题。扩展传统无容量限制的固定费用选址模型, 从抵御设施中断的视角和提高服务质量的视角建立选址布局网络的双目标优化模型, 以应急设施的建立成本和抵御设施中断的加固成本最小为目标, 以最大化覆盖服务质量水平为目标, 在加固预算有限及最大最小容量限制约束下, 构建中断情境下应急设施的可靠性选址决策优化模型。针对所构建模型的特性利用非支配排序多目标遗传算法(NSGA-Ⅱ)求解该模型, 得到多目标的Pareto前沿解集。以不同的算例分析和验证模型和算法的可行性。在获得Pareto前沿的同时对不同中断概率进行灵敏度分析, 给出Pareto最优解集的分布及应急设施选址布局网络的拓扑结构。     

计及多重阻塞的电动汽车移动储能特性建模

为实现城市交通电力耦合系统在城市道路、充电设施、输电线路阻塞环境下的优化运行,提出了计及多重阻塞的动态交通电力流联合优化方法。首先,基于时空网络模型,提出了计及电动汽车移动、静止、充电、排队模式的队列时空网络模型,构建了适用于电动汽车的车辆调度模型,进而形成动态交通分配模型,以减少交通出行损失。其次,通过优化发电机组、储能等的出力和备用计划,计及城市电网安全、备用约束,构建了安全约束动态经济调度模型,以降低碳排放及发电成本。随后,形成多目标动态优化模型,并将其转换为混合整数凸二次规划问题。最后,在耦合IEEE-30、Sioux Falls系统中验证了所提模型的有效性。     

Multi-period reverse logistics network design for used refrigerators

This paper focuses on the design of a multi-stage reverse logistics network for product recovery. Different recovery options such as product remanufacturing, component repairing and material recycling are simultaneously considered. Initially, we propose a mixed integer linear programming model – with a profit maximization objective – for the network design problem. The structure of the product, by way of bill of materials (BOM), is also incorporated into the proposed model in order to analyze the flow at component and material levels. Sensitivity analysis is carried out to study the effects of variations in the values of the input parameters such as product return quantity, unit transportation cost per unit distance, and unit processing cost. The analysis shows that the design decisions of different facilities considerably change even for 5–20%% variations in input parameter values. This led to the development of a refined mathematical model which incorporates variations in the different input parameter values over time. The new model provides a unified design for the entire planning horizon and has been validated with the design of a used refrigerator recovery network.