基于层次任务网络的舰载机任务规划

航空母舰舰载机任务规划问题涉及复杂的资源约束、时态约束、操作规范及设备使用限制,且任务间相互耦合,是一类非确定性难（NP-hard）问题。其计算复杂度随问题规模呈指数增长,采用常规数学建模和求解方法很难解决。针对舰载机任务规划问题,考虑任务的层次性特征,以及时间和空间约束导致的资源冲突,设计资源状态更新机制,提出层次任务网络（Hierarchical Task Network,HTN）规划算法。算例分析结果表明,该规划方法可以充分考虑资源与时间约束,快速为多个带有截止期限的飞行任务提供可行的行动方案。     

基于贝叶斯网络的舰用汽轮滑油泵可靠性定量分析

针对舰用主滑油系统汽轮滑油泵装置,系统研究其结构功能关系及典型的故障模式。基于系统3种典型故障的FTA模型,建立相应的贝叶斯网络模型进行可靠性定量分析。考虑到系统中存在的固有不确定性因素,对模型的条件概率进行合理修正,提高可靠性分析的准确性。运用贝叶斯网络精确推理算法,得出系统可靠性指标和模型中底事件的概率重要度。根据计算结果,分析得到影响系统可靠性较大的关键部件,这些部件需要加强备份和重点监控。     

舰船电力系统中智能电网技术的应用浅析

  目的  由于海面传感器的耗能点分散、负荷波动幅度较大且节能降耗的需求迫切,为了优化能量供给模式,提出面向海面传感器的船载能量网络（SEN）。  方法  首先,基于车载能量网络、动态无线充电技术及电动船舶技术,分析SEN模型的可行性;然后,基于海面传感器的特点,建立SEN模型,提出能量传输最大化和能量损失最小化这2个问题,并定义问题模型和约束函数;最后,通过开源模型MaritimeSim选取基础实验数据集。  结果  实验结果表明,通过合理设置参数,SEN能够将海上可再生能量传输至海面传感器节点,从而补充电力网络并增强其电能传输能力。  结论  研究成果可为优化海面传感器的能量供给提供新的设计方法。     

Network equilibrium models with battery electric vehicles

The limited driving ranges, the scarcity of recharging stations and potentially long battery recharging or swapping time inevitably affect route choices of drivers of battery electric vehicles (BEVs). When traveling between their origins and destinations, this paper assumes that BEV drivers select routes and decide battery recharging plans to minimize their trip times or costs while making sure to complete their trips without running out of charge. With different considerations of flow dependency of energy consumption of BEVs and recharging time, three mathematical models are formulated to describe the resulting network equilibrium flow distributions on regional or metropolitan road networks. Solution algorithms are proposed to solve these models efficiently. Numerical examples are presented to demonstrate the models and solution algorithms.     

Estimating economic and resilience consequences of potential navigation infrastructure failures: A case study of the Monongahela River

The paper examines the potential effects of failure of heavily used, outdated locks and dams on the Monongahela River in southwestern Pennsylvania. Catastrophic failure would result in lengthy outage of barge traffic. The displaced volume of coal shipments from mines to power plants is estimated using Energy Information Administration survey data. The resilience of the impacted facilities, the viability of their shipping alternatives, and their ability to re-organize into new markets is assessed. Lost revenues are estimated for facilities that close due to an inability to adapt, as well as the replacement cost of towboats and barges trapped by a catastrophic and sudden failure. The aggregate costs to these facilities as a result of a year-long closure are estimated at $0.56-1.7 billion.     

Optimization models for differentiating quality of service levels in probabilistic network capacity design problems

This paper develops various chance-constrained models for optimizing the probabilistic network design problem (PNDP), where we differentiate the quality of service (QoS) and measure the related network performance under uncertain demand. The upper level problem of PNDP designs continuous/discrete link capacities shared by multi-commodity flows, and the lower level problem differentiates the corresponding QoS for demand satisfaction, to prioritize customers and/or commodities. We consider PNDP variants that have either fixed flows (formulated at the upper level) or recourse flows (at the lower level) according to different applications. We transform each probabilistic model into a mixed-integer program, and derive polynomial-time algorithms for special cases with single-row chance constraints. The paper formulates benchmark stochastic programming models by either enforcing to meet all demand or penalizing unmet demand via a linear penalty function. We compare different models and approaches by testing randomly generated network instances and an instance built on the Sioux–Falls network. Numerical results demonstrate the computational efficacy of the solution approaches and derive managerial insights.     

Continuous approximation for skip-stop operation in rail transit

Operating speed of a transit corridor is a key characteristic and has many consequences on its performance. It is generally accepted that an increased operating speed for a given fleet leads to reduced operating costs (per kilometer), travel and waiting times (three changes that can be computed precisely), an improved comfort and level of service, which can attract new passengers who are diverted from automobile (items harder to estimate precisely). That is why several operation schemes which aim to increase the operating speed are studied in the literature, such as deadheading, express services, and stop skipping.A novel category of solutions to this problem for one-way single-track rail transit is to perform accelerated transit operations with fixed stopping schedules. The concept is quite simple: as the time required for stopping at each station is an important part of travel time, reducing it would be a great achievement. Particular operations that take advantage of this idea already exist. This paper focuses on one of them: the skip-stop operation for rail transit lines using a single one-way track. It consists in defining three types of stations: AB stations where all the trains stop, and A and B stations where only half of the trains stop (stations type A and B are allocated interchangeably). This mode of operation is already described in the literature (Vuchic, 1973, Vuchic, 1976, Vuchic, 2005) and has been successfully implemented in the Metro system of Santiago, Chile.This work tackles the problem with a continuous approximation approach. The problem is described with a set of geographically dependent continuous parameters like the density of stations for a given line. Cost functions are built for a traditional (all-stop) operation and for skip-stop operation as described above. A simple example is presented to support this discussion. Finally, a discussion about the type of scenarios in which skip-stop operations are more beneficial is presented.     

Data dependent input control for origin–destination demand estimation using observability analysis

In this paper, we address the observability issue of static O–D estimation based on link counts. Unlike most classic observability analyses that relied only on network topological relationships, our analysis incorporates the actual values of input parameters, thus including network operational relations as well. We first analyze possible mathematical properties of an O–D estimation problem with different data input. We then propose a modeling approach based on mixed-integer program for selecting model input that ensures observability and estimation quality. Through establishing a stronger connection between observability analysis and the corresponding estimation problem, the proposed method aims to improve estimation quality while reducing reliance on erroneous data.     

Strategic considerations behind the network–regional airline tie ups – A theoretical and empirical study

The paper examines the strategic vertical relationship between network and regional airlines. We develop a model to illustrate how network airlines can use the contractual relationship with regional airlines as an efficient tool to simultaneously drive out inefficient network airlines and also accommodate other cost efficient network airlines in any specific market. The model is tested on U.S. data using simultaneous and sequential choice models. We find that market size, cost differences between network airlines, as well as cost differences between network and regional airlines, are the chief determinants of the network airlines’ decisions on whether or not to serve a market with their own fleet, as well as how many regional airlines to contract with.