Incessant Allocation Method for Solving Transportation Problems

Industries require planning in transporting their products from production centres to the users end with minimal transporting cost to maximize profit. This process is known as Transportation Problem which is used to analyze and minimize transportation cost. This problem is well discussed in operation research for its wide application in various fields, such as scheduling, personnel assignment, product mix problems and many others, so that this problem is really not confined to transportation or distribution only. In the solution procedure of a transportation problem, finding an initial basic feasible solution is the prerequisite to obtain the optimal solution. Again, development is a continuous and endless process to find the best among the bests. The growing complexity of management calls for development of sound methods and techniques for solution of the problems. Considering these factors, this research aims to propose an algorithm “Incessant Allocation Method” to obtain an initial basic feasible solution for the transportation problems. Several numbers of numerical problems are also solved to justify the method. Obtained results show that the proposed algorithm is effective in solving transportation problems.

Incentive allocation of shared property in transportation industries with network characteristics

Industries with network characteristics always have some special features, which differ from the ordinary business companies. Some scholars hold the theoretical viewpoint that these industries bear the characteristics of natural monopoly, externality, measurement difficulty, etc. However, all these theories can explain why the network industries, especially prominent in transportation industries, are confronted with many difficulties in their process of reform and reorganization. But, there is something deep-seated that can explain why network industries such as railway, highway, aviation, telecommunication, water, gas, etc. have the characteristics of natural monopoly. The paper holds that： （1） Shared property in transportation industries such as the network infrastructure, station and marshalling yard, dispatch and control right, serves more than two enterprises or even hundreds of relative enterprises. （2） Shared property makes it possible for great amount of product quantity to share the sunken cost. Therefore, economy of scale and economy of scope thus exist in transportation sectors, which is called network economy. （3） From the input and output relationships in transportation industries with network features, there exists a law of increasing returns to scale, which is opposite to the classic economy theory that diminishing returns to scale will appear finally. Why？ It is because of the existence of shared property. Not only production cost, but also the transaction cost among transportation enterprises can be reduced. （4） We establish a quantitative model to testify the theory. The implication is that, the lack of incentive allocation is, if not all, one reason causing the usage inefficiency of the rights concerned. The low efficiency manifests in two aspects： the first one is the organization boundary, that is, transportation enterprises are not real enterprises at present. The second one is the so-called mixed task equilibrium of railway affairs. We haven＇t separated the shared property from the private ones.

STUDY ON STRATEGY OF DYNAMIC JOINT ROUTING AND RESOURCE ALLOCATION IN LAYERED OPTICAL TRANSPORT NETWORKS

A layered network model for optical transport networks is proposed in this paper,which involves Internet Protocol(IP) ,Synchronous Digital Hierarchy(SDH) and Wavelength Division Mul-tiplexing(WDM) layers. The strategy of Dynamic Joint Routing and Resource Allocation(DJRRA) and its algorithm description are also presented for the proposed layered network model. DJRRA op-timizes the bandwidth usage of interface links between different layers and the logic links inside all layers. The simulation results show that DJRRA can reduce the blocking probability and increase network throughput effectively,which is in contrast to the classical separate sequential routing and resource allocation solutions.

Optimal Allocation of Public Transport Hub Based on Load Loss Value and the Economy of Distribution Network

The rapid development of electric buses has brought a surge in the number of bus hubs and their charging and discharging capacities.Therefore,the location and construction scale of bus hubs will greatly affect the operation costs and benefits of an urban distribution network in the future.Through the scientific and reasonable planning of public transport hubs on the premise of meeting the needs of basic public transport services,it can reduce the negative impact of electric bus charging loads upon the power grids.Furthermore,it can use its flexible operation characteristics to provide flexible support for the distribution network.In this paper,taking the impact of public transport hub on the reliability of distribution network as the starting point,a three-level programming optimization model based on the value and economy of distribution network load loss is proposed.Through the upper model,several planning schemes can be generated,which provides boundary conditions for the expansion of middle-level optimization.The normal operation dispatching scheme of public transport hub obtained from the middle-level optimization results provides boundary conditions for the development of lower level optimization.Through the lower level optimization,the expected load loss of the whole distribution system including bus hub under the planning scheme given by the upper level can be obtained.The effectiveness of the model is verified by an IEEE-33 bus example.

A Machine-Learning Based Time Constrained Resource Allocation Scheme for Vehicular Fog Computing

Through integrating advanced communication and data processing technologies into smart vehicles and roadside infrastructures,the Intelligent Transportation System(ITS)has evolved as a promising paradigm for improving safety,efficiency of the transportation system.However,the strict delay requirement of the safety-related applications is still a great challenge for the ITS,especially in dense traffic environment.In this paper,we introduce the metric called Perception-Reaction Time(PRT),which reflects the time consumption of safety-related applications and is closely related to road efficiency and security.With the integration of the incorporating information-centric networking technology and the fog virtualization approach,we propose a novel fog resource scheduling mechanism to minimize the PRT.Furthermore,we adopt a deep reinforcement learning approach to design an on-line optimal resource allocation scheme.Numerical results demonstrate that our proposed schemes is able to reduce about 70%of the RPT compared with the traditional approach.

Allocation of Mobile Chippers for a Concentrated Bioenergy Demand

Allocation of mobile chippers is a tactical problem of management in a bioenergy supply chain. It influences the entire supply cost of the wood chip since the transportation distance and the chipping productivity decide the transportation cost. Great and concentrated demands of woody biomass require multiple suppliers, and there should be the best allocation of mobile chippers which minimize the entire supply cost. This study aims to clarify better management of the supply chain consisting of multiple players for a great and concentrated demand for wood chip. The model was a supply chain for a typical biomass power plant with 5.8 MW capacity. Suppliers were assumed to select mobile chippers from two sizes, 140-kW and 353-kW. By the model simulation, it was clarified that the well-considered allocation of two different mobile chippers could reduce the entire supply cost less than the conventional system using a fixed chipper at the power plant. The best management was to use only the 353-kW chippers, and secondly to allocate the less productive chippers closer to the demand to prevent the incline of the transportation cost. However, the possible conflict was also specified as the increased cost of the suppliers using more productive chippers in the second best allocation strategy. This result emphasizes the necessity of resolving such conflict by making the collaborative relationship among stakeholders which has been pointed out by other researches as well to sustain the better condition of the supply chain.

高速铁路列车开行方案与票价票额综合优化

为提升高速铁路的运营组织水平和盈利能力,本文提出高铁列车开行方案与票价票额综合优化方法。首先,构建分时客流需求与票价间弹性需求函数,并分析包括出发时段偏差、乘车耗时及票价的旅客广义出行成本,进而采用多项式Logit模型描述分时弹性客流的列车选择行为。在此基础上,以客票总收入与运营总成本之差最大为目标构建三者综合优化模型。其次,利用OD总收益关于列车票价的偏导构造票价方案搜索策略,使票价邻域解和列车开行方案邻域解相适应,并运用Cplex求解对应的最优票额分配方案,设计模拟退火算法求解模型。最后,基于郑西高速铁路进行算例分析,结果表明:在7个不同弹性系数下进行综合优化,旅客出行成功率和列车平均客座率均在90%以上,优化解的列车开行方案、票价方案及票额分配方案均高度匹配;在5组不同规模算例中,三者综合优化的运营净收益相比于固定票价下的开行方案与票额联合优化和固定开行方案下的票价与票额联合优化,分别提高了4.11%~15.25%和3.17%~13.42%,且人均单位里程出行成本亦分别降低了1.69%~4.96%和0.97%~4.35%,表明综合优化更好地提升了高速铁路的运营收益和旅客服务水平。

考虑海铁联运的集装箱码头泊位分配优化

在海铁联运背景下,协同考虑到港船舶及铁路班列特点,优化集装箱码头泊位分配,对于提高港口作业效率至关重要。在满足码头岸线、泊位水深、岸桥等资源约束前提下,综合考虑船舶服务优先级和偏好泊位、铁路集装箱班列到发时间等约束,以船舶在港停留时间和泊位偏移惩罚时间最小为优化目标,建立海铁联运集装箱码头泊位分配优化模型;针对模型特点,设计自适应遗传算法进行求解,选取计划周期48 h内的到港船舶数据进行案例分析,通过MATLAB数值实验,得到符合船舶服务优先级和泊位偏好要求且契合铁路班列开行计划的海铁联运码头泊位分配方案。数值实验结果表明:在海铁联运协同优化条件下,船舶平均等泊时间为2.9 min,最大等泊时间为11.4 min,同时船舶的靠泊位置与偏好泊位之间的距离均不超过100 m,船舶在港的停留时间及偏好泊位差都得到了较好的控制。研究可进一步优化海铁联运集装箱码头泊位分配方案,有利于提高海铁联运集装箱在港转运效率。

计及全生命周期成本的公交光伏充电站储能优化配置方法

“双碳”目标下城市公交车全面推进电动化,公交光伏充电站面临并网点负载压力大、运营成本高的问题。提出公交光伏充电站储能优化配置方法。基于大量的调研数据分析公交充电负荷特性,构建公交光伏充电站典型运行场景;综合考虑充电站运营商利益、公共交通通勤需求以及并网点的容量限制,构建计及全生命周期成本的公交光伏充电站电池储能优化配置双层模型。以北京某在营公交充电站为算例,验证了所提配置方法的有效性,量化评估了光伏发电余量上网、公交车充电策略、电网电价及电池购置价格等因素对充电站配置储能运营经济性的影响。

铁路枢纽双编组站静态配流协同优化研究

枢纽内跨编组站进行协同配流有助于优化枢纽内的车流接续,提高全局配流质量。引入跨编组站协同配流思想,构建铁路枢纽双编组站静态配流协同优化模型,以最小化双编组站的配流总代价、最大化双编组站的总满轴列车数为优化目标,考虑车流量约束、列车到解编发作业与枢纽小运转列车走行的接续时间约束、出发列车满轴与不违编约束、调机资源使用约束。以列车等级、编组去向数及出发时刻排序作为配流代价。设计理想点算法将多目标转化为单目标进行求解,最后运用算例对模型及算法的有效性进行验证。结果表明,双编组站联合配流相较于两编组站单独配流,可使满轴列车总数增加1列、站存车总数减少13辆、配流总代价降低5.4%,从而达到更佳的配流效果。

面向车次取消的票额分配与停站方案组合优化研究

当列车因严重干扰而取消时,大量旅客将在车站滞留,同时铁路公司收益也会受到一定影响,合理的票额分配是解决此类问题的有效方法。在差异化设置换乘旅客优先权基础上,构建了以铁路公司收益最大化和偏离原时刻表最小化为目标的票额分配和停站方案组合优化模型,并通过增加不等式组约束条件将其线性化;利用求解器GUROBI对上述模型进行求解并分析算例。研究结果表明:当列车因干扰而取消时,与不采用任何措施相比,灵活停站策略能有效地减少滞留旅客数量19.7%以上;铁路公司收益增加21.8%以上。

基于区块链的城市智能交通网络均衡分配方法

为了提高城市智能交通网络的应用效率,有效分配网络中存在的资源,同时保证网络资源分配的均衡度。因此,提出区块链技术下城市智能交通网络均衡分配方法。通过建立城市智能交通网络模型,分析用户在交通网络中的资源需求。根据用户的需求,采用区块链技术分配网络中的资源,通过引入椭圆曲线数字签名算法,对需求和资源的发布信息加密处理,并根据资源需求与资源供应之间的匹配,完成城市智能交通网络资源的均衡分配。实验结果表明,所提方法的用户吞吐率高,且Jain公平指数在0.8以上,表明所提方法的资源分配合理性高。

考虑航空公司偏好的协同航路分配优化方法

为提高协同决策中管制与航空公司之间的参与,减少航班的延误,提出多目标下的考虑航空公司偏好的航迹时隙分配模型,解决具有多个受限区的航路资源分配问题。该模型以满足容量限制、最小化航班延误及改航的相关成本为效率和公平性目标,将该模型应用于国内某航路实例数据,运用Benders分解算法分析求解模型。结果表明,与传统的地面等待方法相比,航班总延误成本每分钟显著降低6.2%,由于改航分配导致地面延误减少,使航班总延误时间降低了29.3%,这一结果强调,增加改航(除了地面等待)以避免空域受限区的重要性。此外,该模型允许航空公司能够根据自身偏好灵活地选择原计划航线或替代航线,分析航空公司的偏好对个人和系统延误水平的影响。最后,讨论基于不同公平方案下多受限资源分配过程中效率与公平之间的权衡,提出的Min-Max方法相比现有的RBS(Ration-By-Schedule)方法能够使空域运行效率提高5.4%,航空公司公平性提高70.8%。可见,提出的多目标协同航路分配优化方法的有效性,在降低总延误成本的基础上兼顾各航空公司的公平性,是解决协同航路资源分配问题的一种有效方法。

考虑用户偏好的停车场共享泊位分配模型

城镇化、机动化的持续快速发展催生了城市停车问题,为缓解日益严峻的停车窘境,共享停车应运而生并受到广泛关注与研究。为弥补经典共享泊位分配模型对用户停车成本刻画及用户效益评价的缺失,基于共享停车既有研究及调研数据,构建共享停车选择意愿结构方程模型以分析用户偏好,标定结果显示:模型识别出停车费用、步行距离、违停罚款、寻停时间四类停车偏好,且路径系数依次降低。将结构方程模型识别结果及路径系数作为用户停车成本建模的依据,以经营平台收益与用户停车成本的差值表示系统效益,将系统效益最大化作为优化目标,综合泊位时空间约束,提出考虑用户偏好的停车场共享泊位分配模型。设计随机生成分配方案的蒙特卡洛算法,定义平台让利程度以评价用户效益。数值算例表明:设计的蒙特卡洛算法能够有效求解模型,在模拟次数约10000次后得到系统效益最大值;考虑用户偏好的停车场共享泊位分配模型能够将用户效益提升约7.5%,为共享经营平台权衡自身收益及用户效益提供一定的理论参考。

中原城市群交通基础设施建设对区域经济发展的空间溢出效应

利用空间杜宾模型和中介效应模型对交通基础设施影响区域经济发展的空间溢出效应和作用机制进行了实证分析。结果表明,中原城市群高速交通网络的建设对区域经济发展的空间溢出效应显著,但不同类型的高速路网对该区域经济发展的影响存在较大的差异:高速公路建设对区域经济发展存在显著的负向的本地效应和空间溢出效应,高速公路建设加大了资源配置的扭曲,其市场整合效应也对现阶段中原城市群各城市经济发展造成了负向影响;高速铁路建设对中原城市群各城市经济发展存在显著的正向的本地效应和空间溢出效应,高速铁路的建设显著提升了劳动力配置效率,促进知识溢出提升了科技创新水平,推动了本地和邻近地区的经济发展。

盐碱胁迫对骏枣养分吸收、积累及运转的影响

为揭示基于树体养分吸收、利用与积累特征的骏枣耐盐碱适应性生理机制,通过测定不同浓度盐碱处理下10年生骏枣各器官中N、P、K、Ca、Mg、Fe、Mn、Zn、Cu、Na等矿质元素的含量,分析养分在骏枣不同器官中的吸收、积累与运输分配特征。结果表明:矿质离子在盐碱胁迫下主要集中在主根、多年生枝,有无盐碱胁迫时Na^(+)都主要聚集在主根中,K+浓度在叶片中最高,可以保持较高的K+/Na^(+)。在低浓度盐碱胁迫(60 mmol·L^(-1))下Mg、Ca的运输能力增强;高浓度盐碱胁迫(180 mmol·L^(-1))下须根至叶片的Mg、Ca运输能力分别显著下降44.7%和33.1%,叶片中Ca^(2+)/Na^(+)、Mg^(2+)/Na^(+)值分别显著降低72.8%和71.6%,但仍大于1;其他器官中K+/Na^(+)、Ca^(2+)/Na^(+)、Mg^(2+)/Na^(+)保持稳定且大于1。相较于CK,高浓度盐碱胁迫下当年生枝中的Mn、Fe含量与多年生枝中的Mg含量分别升高了14.01%、11.11%、10.52%,Cu、Zn、Mn、Fe在须根中的含量分别升高了117.53%、25.65%、84.98%、26.19%,主根中N、P、Zn、Mn、Fe、Ca的含量分别下降了23.07%、15.38%、80.48%、49.58%、8.82%、30.44%。结果表明成年骏枣树的盐适应机制主要是通过根对Na^(+)的聚积作用,以及叶对K、Mg和Ca的选择性吸收能力增强来实现的。

考虑旅客有限理性的城际公交化列车开行频率优化

列车开行频率优化对提升城际铁路公交化运营收益水平和旅客满意度具有重要意义。通过分析有限理性条件下的乘车选择行为,构建了有限理性条件下城际铁路客流分配模型;通过构建列车候选集,以基于客流分配的列车客流与开行频率相关的成本为目标,考虑开行客流条件、客流守衡和区间运力等为约束,构建基于列车候选集与旅客有限理性的城际公交化列车开行频率多目标优化模型,并设计了一种NSGA—II算法进行求解。以长株潭城际公交化铁路为例验证模型和算法的有效性,并通过关键参数扰动分析,揭示不同客流OD和客流条件阈值对开行频率方案的影响机理。研究结果表明:在考虑旅客和企业双方效益下,开行频率方案更具多样性,且随开行频率增加,二者间的制约作用显著。随客流OD增大,模型解空间缩小,算法收敛性和解集多样性降低,优化梯度更倾向于增开站站停列车。此外,随客流阈值增加,有限理性行为对优化方案影响甚微,企业成本大幅降低。本研究可为铁路运营企业在城际公交化运营中的管理与决策提供参考。

运销分离下的天然气管网运输能力分配优化研究

基于中国天然气管网当前采用的合同路径法,即“点对点”交易模式,提出一种适应于多气源多用户的管网基础设施容量分配优化方法,采用分布式优化策略对托运商子模型与管网公司子模型进行迭代求解,最终实现各托运商输气计划与天然气管网调度能力的匹配。结果表明:提出的分布式优化策略能够协调多方利益,托运商单位天然气成本仅与气源及用户位置分布相关,能够一定程度上保证分配结果的公平性;中国天然气管网区域间仍存在输送瓶颈,运销分离将导致管输路径及容量的激烈竞争,引发天然气管输合同拥塞问题,造成局部管道负荷率较高;在实际案例中管道基础设施容量的市场化分配导致托运商购气成本增加6.94%,管输服务费用增加10.18%,总体运营成本增加了6.80%,提高了管网公司收益,但不利于降低终端用户成本。

“双碳”目标下的中国公路货运碳交易机制研究

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