多方式弹性需求下公交定价双层规划模型

为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。     

区域立体物流网络规划模型与算法

提出长株潭区域立体物流网络建构及其网络优化设计.精细化定义了模式分担率,构建了更切合实际的双准则双层规划模型.下层规划描述各核心城市物流枢纽间基于多模式多层阶交通条件下的用户选择行为,上层规划追求最小化长株潭区域立体物流网络系统广义物流费用并最大化整个网络的物流运输量,以满足城市群区域经济发展对物流提出的更高要求.给出了可以克服Frank-Wolfe方法缺陷的惩罚Lagrange对偶方法求解下层规划算法,设计了基于实数编码和组合变异的双层规划改进遗传算法,算法可以保证搜索到近似全局最优解.     

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。     

一类多个下层的双层规划问题

本文研究了一类多个下层的双层规划问题.利用文[1]有关理论与方法,获得了该类多下层双层规划问题与一类广义纳什均衡问题的联系,然后通过寻找该广义纳什均衡问题的均衡点求解该双层规划问题.同时给出了一种求解此类广义纳什均衡问题的算法,并进行了一定的理论分析与数值计算.     

恐怖分子入侵阻止网络的双层规划建模与禁忌搜索分析

“一带一路”战略加深了我国与邻国的合作交流,也为境外恐怖分子的潜入提供可乘之机。为防止恐怖分子潜入,提出一类新的恐怖分子入侵阻止网络设计问题,充分考虑恐怖分子的计算能力,通过决策有限安检资源在边境交通网络中的最优分配来降低袭击风险。首先,将该问题构造为双层规划模型,上层规划是政府的阻止网络设计问题,下层规划是恐怖分子的袭击节点选择和入侵路径优化问题;其次,设计一类用禁忌搜索处理上层规划,并结合下层规划直接求解的混合算法;最后,结合南疆实例进行仿真分析,结果发现:恐怖分子计算能力越强,网络城市节点受袭风险越大;政府最优阻断方案随恐怖分子计算能力强弱变化而变化,但存在一定共性原则;增加阻断资源投入可降低袭击风险,但两者存在“边际效用递减”关系。     

基于两阶段启发式算法的物流配送选址-路径问题研究

为了解决配送中心选址与带时间窗的多中心车辆路径优化组合决策问题,利用双层规划法建立了配送中心选址与车辆路径安排的多目标整数规划模型,针对该模型的特点,采用两阶段启发式算法进行了求解。首先,通过基于聚集度的启发式算法对客户进行分类,确定了备选配送中心的服务范围;然后,基于双层规划法,以配送中心选址成本最小作为上层规划目标,以车辆配送成本最小作为下层规划目标,建立了多目标整数规划模型;最后,利用改进的蚁群算法进行了求解。通过分析实例数据和Barreto Benchmark算例的实验结果,验证了该模型的有效性和可行性。     

弹性需求下城市公交网络服务的优化

对具有弹性需求的城市公交网络系统进行了票价结构与发车频率组合的优化。考虑到公交定价和发车频率会影响乘客需求以及乘客对路径的选择行为,将这一问题描述为一个双层规划问题,上层是寻求社会福利最大的优化问题;下层考虑了乘客的出行选择行为,为弹性需求下乘客在城市公交网络上流量分布的随机用户平衡分配模型。鉴于双层规划问题的非凸性,运用模拟退火算法对模型进行求解,并给出一个仿真算例说明提出的模型和算法的合理性。     

基于Benders分解算法的反恐应急设施选址-定容-分配问题

反恐应急设施的合理布局和资源配置可缩短救援到达时间并提高应急效率。对已有反恐应急设施选址研究拓展，进一步考虑设施容量有限的情形，并将袭击前后关于应急设施的选址、定容和救援物资分配问题进行集成考虑。将该问题构造为三层规划模型，上中下各层规划分别对应袭击前的选址定容问题、袭击时的袭击点选择问题和袭击后的救援物资分配问题。利用下层规划的对偶变换转化为双层规划，并设计Benders分解算法求解。最后，结合南疆交通网络进行仿真分析，验证了模型和算法的有效性。     

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。     

混合动力公交车能量控制策略的优化模型

针对混合动力公交车在循环工况内功率需求的特点,建立了未来功率需求贝叶斯预测模型;利用2-阶段随机动态规划模型将大规模的随机动态规划问题简化为多个小规模的随机动态规划问题和一个确定型动态规划问题;对于随机动态规划模型的求解,给出了稀疏表示的降维方法,将复杂的泛函极值问题转化为常规的随机动态优化问题,并采用分布估计算法和计算资源最优配置算法的计算机仿真优化算法对随机动态优化问题进行求解;给出了基于查表的在线控制策略,为模型的实际应用进行了有益的探索。     

Parking Capacity and Pricing in Park'n Ride Trips: A Continuous Equilibrium Network Design Problem

In this paper we consider the problem of designing parking facilities for park'n ride trips. We present a new continuous equilibrium network design problem to decide the capacity and fare of these parking lots at a tactical level. We assume that the parking facilities have already been located and other topological decisions have already been taken.The modeling approach proposed is mathematical programming with equilibrium constraints. In the outer optimization problem, a central Authority evaluates the performance of the transport network for each network design decision. In the inner problem a multimodal traffic assignment with combined modes, formulated as a variational inequality problem, generates the share demand for modes of transportation, and for parking facilities as a function of the design variables of the parking lots. The objective is to make optimal parking investment and pricing decisions in order to minimize the total travel cost in a subnetwork of the multimodal transportation system.We present a new development in model formulation based on the use of generalized parking link cost as a design variable.The bilevel model is solved by a simulated annealing algorithm applied to the continuous and non-negative design decision variables. Numerical tests are reported in order to illustrate the use of the model, and the ability of the approach to solve applications of moderate size.     

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。     

具有两种运输方式选择的物流排序问题

本文研究了单机环境下,有两种运输方式可供选择的集成生产和运输的排序问题。有多个工件需要在一台机器上进行加工,工件生产完后需要分批运到客户处。有两种运输方式,普通运输和特快运输可供选择。制造商需要安排工件的加工顺序,选择合适的运输方式和出发时间,以极小化相应的时间目标与运输费用的加权和。研究了排序理论中主要的两个目标函数,分析了问题的复杂性,对于这些问题给出了它们的最优算法。     

Tree network design avoiding congestion

We introduce in this paper an optimal method for tree network design avoiding congestion. We see this problem arising in telecommunication and transportation networks as a flow extension of the Steiner problem in directed graphs, thus including as a particular case any alternative approach based on the minimum spanning tree problem. Our multi-commodity formulation is able to cope with the design of centralized computer networks, modern multi-cast multi-party or hub-based transportation trees. The objective in such cases is the minimization of the sum of the fixed (structural) and variable (operational) costs of all the arcs composing an arborescence that links the origin node (switching center, server, station) to every demand node (multi-cast participants, users in general). The non-linear multi-commodity flow model is solved by a generalized Benders decomposition approach.     

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.     

Uncertain solid transportation problems

The solid transportation problem arises when bounds are given on three item properties. Usually, these properties are source, destination and type of product or mode of transport, and often are given in a uncertain way. This paper deals with two of the ways in which uncertainty can appear in the problem: Interval solid transportation problem and fuzzy solid transportation problem. The first arises when data problem are expressed as intervals instead of point values, and the second when the nature of the information is vague. Both models are treated in the case in which the uncertainty affects only the constraint set. For interval case, an auxiliary problem is obtained in order to find a solution. This auxiliary problem is a standard solid transportation problem which can be solved with the efficient methods existing. For fuzzy case, a parametric approach which makes it possible to find a fuzzy solution to the former problem is used.     

区域废弃物网络系统的选址-运输优化模型

区域废弃物网络系统优化设计包括设施的选址和废弃物运输路线的确定。考虑了多类型设施、多种废弃物流和模糊数形式的废弃物产生量,建立了模糊机会约束规划模型来求得整个系统的优化配置。通过将模型中的机会约束清晰化,将模糊机会约束规划模型转化成等价的确定模型来求解。实例表明了模型的有效性。     

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.     

A technique for speeding up the solution of the Lagrangean dual

We propose techniques for the solution of the LP relaxation and the Lagrangean dual in combinatorial optimization and nonlinear programming problems. Our techniques find the optimal solution value and the optimal dual multipliers of the LP relaxation and the Lagrangean dual in polynomial time using as a subroutine either the Ellipsoid algorithm or the recent algorithm of Vaidya. Moreover, in problems of a certain structure our techniques find not only the optimal solution value, but the solution as well. Our techniques lead to significant improvements in the theoretical running time compared with previously known methods (interior point methods, Ellipsoid algorithm, Vaidya's algorithm). We use our method to the solution of the LP relaxation and the Langrangean dual of several classical combinatorial problems, like the traveling salesman problem, the vehicle routing problem, the Steiner tree problem, thek-connected problem, multicommodity flows, network design problems, network flow problems with side constraints, facility location problems,K-polymatroid intersection, multiple item capacitated lot sizing problem, and stochastic programming. In all these problems our techniques significantly improve the theoretical running time and yield the fastest way to solve them.     

Impact analysis of maritime cabotage legislations on liner hub-and-spoke shipping network design

Maritime cabotage is a legislation published by a particular coastal country, which is used to conduct the cargo transportation between its two domestic ports. This paper proposes a two-phase mathematical programming model to formulate the liner hub-and-spoke shipping network design problem subject to the maritime cabotage legislations, i.e., the hub location and feeder allocation problem for phase I and the ship route design with ship fleet deployment problem for phase II. The problem in phase I is formulated as a mixed-integer linear programming model. By developing a hub port expanding technique, the problem in phase II is formulated as a vehicle routing problem with pickup and delivery. A Lagrangian relaxation based solution method is proposed to solve it. Numerical implementations based on the Asia–Europe–Oceania shipping services are carried out to account for the impact analysis of the maritime cabotage legislations on liner hub-and-spoke shipping network design problem.