The total cost bounds of the transportation problem with varying demand and supply

A transportation problem is a linear programming problem based on a network structure consisting of a finite numbers of nodes and arcs attached to them. In real world applications, the supply and demand quantities in the transportation problem are sometimes hardly specified precisely because of changing economic conditions. This paper investigates the transportation problem when the demand and supply quantities are varying. A pair of mathematical programs is formulated to calculate the objective value. The derived result is also in range, where the total transportation cost would appear. In addition to allowing for simultaneous changes in supply and demand values, the total cost bounds are calculated directly. Due to the structure of the transportation problem, the largest total transportation cost may not occur at the highest total quantities shipped. Since the total cost bounds are derived, it would be beneficial to decision-making.     

A Public Transportation Decision‐Making Model within a Metropolitan Area

Understanding the decision‐making factors associated with public transportation is essential in strategic development of public transportation to improve acceptance and utilization of mass transit systems. This research analyzes factors affecting attitudes toward public transportation and the choice of transportation mode by investigating the public transportation decision‐making process of working professionals using a survey methodology. The objectives of this research are to model the transportation decision‐making process of public transportation users in a metropolitan area and to determine key factors that affect the public transportation choices made by potential public transportation users. This study contributes to the literature by developing and testing an integrated theoretical framework for modeling an individual's public transportation decision‐making process using four independent variables: Perceived Public Transportation Security, Knowledge, Price, and Convenience. We develop the proposed theoretical framework based upon the extant literature and tested it using partial least squares structural equation modeling (PLS‐SEM). Based on the Theory of Reasoned Action, the Theory of Planned Behavior, and utility theory, we develop the factors and refine associated items using confirmatory factor analysis.     

具有批量折扣的供应物流网络优化遗传算法研究

针对具有批量折扣和转运的供应链优化问题的特征,提出供应物流网络概念及其优化参数:节点、线路和流量;根据包括采购和物流的供应总成本函数最小化,建立供应物流网络优化问题的数学模型;设计此类优化问题的遗传算法,通过仿真算例,说明和验证遗传算法对该问题具有很好的可行性和实用性.     

A memetic algorithm for the patient transportation problem

This paper addresses a real-life public patient transportation problem derived from the Hong Kong Hospital Authority (HKHA), which provides ambulance transportation services for disabled and elderly patients from one location to another. We model the problem as a multi-trip dial-a-ride problem (MTDARP), which requires designing several routes for each ambulance. A route is a sequence of locations, starting and terminating at the depot (hospital), according to which the ambulance picks up clients at the origins and delivers them to the destinations. A route is feasible only if it satisfies a series of side constraints, such as the pair and precedence constraints, capacity limit, ride time, route duration limit and time windows. Owing to the route duration limit, in particular, every ambulance is scheduled to operate several routes during the working period. To prevent the spread of disease, the interior of the ambulances needs to be disinfected at the depot between two consecutive trips. The primary aim of the problem investigated herein is to service more requests with the given resources, and to minimize the total travel cost for the same number of requests. In this paper, we provide a mathematical formulation for the problem and develop a memetic algorithm with a customized recombination operator. Moreover, the segment-based evaluation method is adapted to examine the moves quickly. The performance of the proposed algorithm is assessed using the real-world data from 2009 and compared with results obtained by solving the mathematical model. In addition, the proposed algorithm is adapted to solve the classic DARP instances, and found to perform well on medium-scale instances.     

多级供应链系统成本分析随机网络模型及算法研究

供应链成本管理是企业战略管理的核心组成部分。为研究多级供应链网络系统的成本组成及其分布特征、分析各节点企业的成本管理对多级供应链网络系统的影响、找到供应链系统成本管理中的薄弱环节和关键企业,本文构建了多级供应链系统成本的随机网络分析模型。首先研究了模型的结构性质特征,给出成本分布特征的解析算法。然后扩展模型,分别从系统成本类型构成(生产成本、库存成本和物流成本)和系统对企业成本波动的灵敏度两个角度深入研究多级供应链网络成本问题。数值算例分析结果说明了多级供应链网络系统成本分析模型和相关算法的有效性和实用性。     

Eco-efficient supply chain networks: development of a design framework and application to a real case study

This paper presents a supply chain network design framework that is based on multi-objective mathematical programming and that can identify ‘eco-efficient’ configuration alternatives that are both efficient and ecologically sound. This work is original in that it encompasses the environmental impact of both transportation and warehousing activities. We apply the proposed framework to a real-life case study (i.e. Lindt & Sprüngli) for the distribution of chocolate products. The results show that cost-driven network optimisation may lead to beneficial effects for the environment and that a minor increase in distribution costs can be offset by a major improvement in environmental performance. This paper contributes to the body of knowledge on eco-efficient supply chain design and closes the missing link between model-based methods and empirical applied research. It also generates insights into the growing debate on the trade-off between the economic and environmental performance of supply chains, supporting organisations in the eco-efficient configuration of their supply chains.     

多枢纽轴辐式协同物流网络任务-路径优化匹配研究

针对物流网络运营中规模效益低、运营商与客户利益冲突等问题，本文提出了基于多枢纽轴辐式协同物流网络的任务-路径优化匹配策略。在网络结构确定的条件下，从物流集成服务商角度出发，综合考虑资源发车时刻、路径能力限制、动态成本折扣系数以及任务延时惩罚，构建了以总物流成本最小和时间最短为优化目标的轴辐式协同物流网络任务-路径优化匹配数学模型。根据问题特点，设计了基于三层编码的遗传算法对模型进行求解，同时配合多点交叉、变异机制提高求解效率。研究结果表明，集并运输能够大幅度降低任务集执行成本，但当集并带来的交货延迟、客户满意度降低等负面效应超过其正面效应时，需适当匹配直达线路以提高整体效益。     

一种求解时变网络下多式联运最短路的算法

在运输过程中,往往不止有一种运输方式,可能同时有多种运输方式交叉,即可能多式联运的方式存在,不同的运输方式之间需要通过转运才可实现.同时,在运输过程中,成本、运输时间、风险等因素会随着时间的不同而变化.首先,将运输网络进行变形,然后给出了在时变网络条件下多式联运的最短路模型,设计了求解时变条件下多式联运的最短路的算法,利用此算法可以获得从起点到终点之间的最短路,并对算法的计算复杂性进行了分析.最后给出一个应用算例.     

An Approach to Assessing the Impacts of Incident-Free Transportation of Radioactive Materials: II. Highway Transportation

Annual radiation doses and risks to the public living near, and traveling on, public highways, and occupational doses are calculated for highway shipments of radioactive materials under accident-free and incident-free conditions (i.e., under normal transportation conditions). The database developed by Sandia National Laboratories is used, and calculations are made using RADTRAN 4.0. This report is one of two reports estimating radiological risk associated with transportation of radioactive materials.     

具有网络外部性的扩展Hotelling模型

将网络外部性引入线性运输成本下的Hotelling模型,研究了两家网络产品厂商首先选址,然后进行价格竞争的两阶段完全信息动态博弈问题,得到了厂商价格竞争均衡的存在性条件,推广了一般Hotelling模型的结论.由于网络外部性的存在,消费者效用是相互依赖的.网络产品的市场份额既是消费者选择的结果,又是消费者选择的依据.文章将交通流量分配技术和无穷维变分方法相结合,建立了刻画网络产品市场划分的模型——无穷维变分不等式,并研究了市场划分的存在性和唯一性问题.最后假定厂商定位在两端,分析了产品的网络外部性特征及单位运输成本对两个厂商竞争均衡情况的影响.     

Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events

Evacuating residents out of affected areas is an important strategy for mitigating the impact of natural disasters. However, the resulting abrupt increase in the travel demand during evacuation causes severe congestions across the transportation system, which thereby interrupts other commuters' regular activities. In this article, a bilevel mathematical optimization model is formulated to address this issue, and our research objective is to maximize the transportation system resilience and restore its performance through two network reconfiguration schemes: contraflow (also referred to as lane reversal) and crossing elimination at intersections. Mathematical models are developed to represent the two reconfiguration schemes and characterize the interactions between traffic operators and passengers. Specifically, traffic operators act as leaders to determine the optimal system reconfiguration to minimize the total travel time for all the users (both evacuees and regular commuters), while passengers act as followers by freely choosing the path with the minimum travel time, which eventually converges to a user equilibrium state. For each given network reconfiguration, the lower‐level problem is formulated as a traffic assignment problem (TAP) where each user tries to minimize his/her own travel time. To tackle the lower‐level optimization problem, a gradient projection method is leveraged to shift the flow from other nonshortest paths to the shortest path between each origin–destination pair, eventually converging to the user equilibrium traffic assignment. The upper‐level problem is formulated as a constrained discrete optimization problem, and a probabilistic solution discovery algorithm is used to obtain the near‐optimal solution. Two numerical examples are used to demonstrate the effectiveness of the proposed method in restoring the traffic system performance.     

Multimodal hub location and hub network design

Through observations from real life hub networks, we introduce the multimodal hub location and hub network design problem. We approach the hub location problem from a network design perspective. In addition to the location and allocation decisions, we also study the decision on how the hub networks with different possible transportation modes must be designed. In this multimodal hub location and hub network design problem, we jointly consider transportation costs and travel times, which are studied separately in most hub location problems presented in the literature. We allow different transportation modes between hubs and different types of service time promises between origin–destination pairs while designing the hub network in the multimodal problem. We first propose a linear mixed integer programming model for this problem and then derive variants of the problem that might arise in certain applications. The models are enhanced via a set of effective valid inequalities and an efficient heuristic is developed. Computational analyses are presented on the various instances from the Turkish network and CAB data set.     

A Model for the Transportation of Hazardous Waste*

Many decision problems, such as the transportation of hazardous waste, can be modeled by networks. However, due to the imprecise nature of much of the information decision makers have available, it is sometimes difficult to determine a best approach to the problem. To alleviate this problem, a network model that combines both precise and imprecise information is presented for the transportation of hazardous waste. The properties of the network model are investigated and solution procedures are presented.     

可变车道的道路交通网络设计优化方法

城市交通流的潮汐性特点造成上、下班高峰期内,道路资源利用的不合理现象:部分道路一个方向交通严重拥挤,而另一个方向几乎没有交通流量。为了合理利用道路资源,缓解交通拥挤,本文提出了双向流量不平衡道路的车道调整方法,并建立了离散双层规划模型,其中处于上层的交管部门通过调整双向道路的车道分配方案,使得整个城市交通网络的系统总阻抗最小。然后本文给出了该双层规划模型的混沌优化方法,最后以经典的SiouxFalls网络为例验证了本文所提方法的有效性。     

随机需求直接发运的运输与库存整合优化研究

分销系统的运输与库存整合优化是供应链管理的重要研究课题.本文分析了随机需求两级分销系统的三种配送策略,并具体给出了基于整车直接发运策略的运输决策与库存控制整合优化数学模型,可得到最优的两级最优库存水平和最优的运输频率.最后对给出的算例,利用MATLAB7的规划求解功能容易获得了问题的最优解.     

城市低碳交通体系对能源消费结构的影响研究——来自中国十四个城市的面板数据经验

节能减排的重要性已成为国际社会的共识,我国也积极改善城市公共交通体系来控制碳排放。本文搜集了中国十四个城市近10年的面板数据,构建随机效应变系数模型,研究了城市低碳交通体系发展对能源消费结构的影响,研究发现：政府可以利用公共交通定价策略影响消费者偏好,从而实现能源消费结构的优化;城市低碳交通体系中轨道交通对能源消费结构优化有显著性促进作用;公共汽（电）车对能源消费结构的影响会随城市发展程度增加而降低;交通部门可通过限行、限购及加收停车费等方式提高传统汽车购买及出行成本,影响私人汽车保有量,从而减少能源消费结构优化的阻碍。政府应该加大财政补贴力度,补贴由购置补贴转向研发和运营基础设施补贴,改善轨道交通及合理的公共汽（电）车运营体系,提高新能源汽车研发投入,鼓励高能量密度低电耗技术的发展,提高居民对新能源乘用车的需求,优化能源消费结构。     

基于双层规划的区域港口内陆运输网络优化决策

为了对区域港口内陆运输网络进行优化决策,运用双层规划模型对区域港口物流系统中内陆集散中心和运输网络的选择进行决策.并提出求解该模型的对偶协调算法.最后运用算例进行实际分析,结果表明:该模型及其算法具有实用性和可操作性.     

一类仓库/零售商供应链运输问题的数学模型与算法研究

本文主要研究一类二级供应链中的运输问题,这里是指由若干仓库和零售商组成的供应链,物品从仓库运出,到达客户,以满足客户的需求.分单仓库、多仓库和多产品三种情形分别建立数学模型,设计相应的近似算法,并通过实例讨论了算法的有效性.     

运输网络运量分配问题的模型及算法研究

针对我国在运量分配模型及算法方面研究比较薄弱的现状,本文对此问题进行了系统深人的研究,应用运筹学、计算机科学的新的理论和方法,建立了多目标运量分配优化模型,且在模型中,将一些重要特性考虑成运输流量的函数,从而可使分配结果更符合实际情况。同时为求解该模型,本文研究设计了鲁棒性强、高效、实用的自适应搜索算法。     

Review of Regulatory Emphasis on Transportation Safety in the United States, 2002–2009: Public versus Private Modes

The U.S. Department of Transportation is responsible for implementing new safety improvements and regulations with the goal of ensuring limited funds are distributed to where they can have the greatest impact on safety. In this work, we conduct a study of new regulations and other reactions (such as recalls) to fatal accidents in several different modes of transportation implemented from 2002 to 2009. We find that in the safest modes of commercial aviation and bus transport, the amount of spending on new regulations is high in relation to the number of fatalities compared to the regulatory attention received by less safe modes of general aviation and private automobiles. Additionally, we study two major fatal accident investigations from commercial aviation and two major automotive recalls associated with fatal accidents. We find differences in the cost per expected fatality prevented for these reactions, with the airline accident investigations being more cost effective. Overall, we observe trends in both the automotive and aviation sectors that suggest that public transportation receives more regulatory attention than private transport. We also observe that the types of safety remedies utilized, regulation versus investigation, have varying levels of effectiveness in different transport modes. We suggest that these differences are indicative of increased public demand for safety in modes where a third party may be held responsible, even for those not participating in the transportation. These findings have important implications for the transportation industry, policymakers, and for estimating the public demand for safety in new transport modes.