浅谈新常态下海员的现状与可持续发展

海员是我国从海洋大国向海洋强国转变的中流砥柱,他们为发展国民经济、保证航运安全和扩大对外开放做出了巨大的贡献。但是从当前形势来分析,我国对海员的教育培训力度和关怀力度却远远跟不上海洋经济的发展。文中主要指出我国海员目前所面临的发展现状,结合国外海员的发展模式及可吸取的经验,对我国海员的可持续发展做出较为全面的策略探讨。     

A rolling horizon algorithm for auto-carrier transportation

This paper introduces a rolling horizon algorithm to plan the delivery of vehicles to automotive dealers by a heterogeneous fleet of auto-carriers. The problem consists in scheduling the deliveries over a multiple-day planning horizon during which requests for transportation arrive dynamically. In addition, the routing of the auto-carriers must take into account constraints related to the loading of the vehicles on the carriers. The objective is to minimize the sum of traveled distances, fixed costs for auto-carrier operation, service costs, and penalties for late deliveries. The problem is solved by a heuristic that first selects the vehicles to be delivered in the next few days and then optimizes the deliveries by an iterated local search procedure. A branch-and-bound search is used to check the feasibility of the loading. To handle the dynamic nature of the problem, the complete algorithm is applied repeatedly in a rolling horizon framework. Computational results on data from a major European logistics service provider show that the heuristic is fast and yields significant improvements compared to the sequential solution of independent daily problems.     

马达加斯加武海马尔墓地的发掘与研究

马达加斯加武海马尔墓群有近六百座墓,其墓葬形制与同时期东非地区阿拉伯穆斯林的墓葬形制有着明显的不同,有些墓葬与中国穆斯林的墓葬形制有较多相似之处。部分墓葬中出土了大量元、明时期的瓷器和其他随葬品,反映出武海马尔墓群主人可能是元、明时期来自中国东南沿海地区或东南亚的色目、回回商人,以及附属于他们的汉人、马来人或武海马尔当地土著,如他们的妻妾、子女、随从、伙计等,其中有些是受雇于穆斯林商人的汉人或者受穆斯林影响的汉人,因此,其葬俗保留了一些中国传统丧葬礼仪的痕迹。     

Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach

Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.     

地铁道岔尖轨线型复核及矫正

地铁道岔尖轨是道岔实现转换功能的主要部件之一，尖轨线型不良不仅使列车产生晃动，也会影响与基本轨的正常靠贴和自由状态平面位置。尖轨与基本轨靠贴时存在离缝、卡阻和尖轨原始位置不准，会使尖轨失去稳定刚度和增大道岔锁闭“框动”、转换动力以及出现转换反弹现象，继而恶化通号转辙设备的工况，影响道岔的正常使用。由此，轨道专业人士应高度重视尖轨的线型控制。在实践的基础上，认真分析尖轨从生产制造、运输、存放、上道使用过程中线型发生不良变化的成因，提出相应对策措施；并介绍尖轨线型的检测复核和矫正手段。其中，首次倡导“一弦矢距法”检测复核整根尖轨线型的现状，特别针对曲线型尖轨，通过建立数学模型计算得到“一弦”条件下尖轨各检测点理论矢距值，为尖轨上道前进行预矫正提供了依据，这对地铁停运后的有限时间天窗内圆满完成尖轨更换作业意义重大。     

公路建设项目征地拆迁补偿费用确定与控制方法研究

文中以广东省公路建设项目征地拆迁费用的确定为例,以现行实施的征地拆迁补偿相关规定为基础,探讨征地数量和标准的计量、计算方法,建立征地拆迁标准动态数据库,以期对征地拆迁费用的确定和控制提供思路和实际操作指导。     

基于多旅行商问题的应急设施服务区划分模型

基于多旅行商问题，增设集散中心需求及应急服务设施资源容量约束条件，以最小化遍历区域内全部集散中心的综合旅行时间成本为优化目标，构建一种应急设施服务区划分模型，确定各应急设施的服务区范围.设计一种复合算法求解模型，首先基于P-中值选址模型的优化理念，形成初始方案；继而加入禁忌搜索算法，结合LKH求解器对模型进行迭代优化求得最优解.基于宁波市北仑区实际拓扑网络进行案例分析，验证了模型和求解方法的有效性.     

车辆隔热壁K值计算中空气层的处理方法

对轨道交通车辆多层复合结构的隔热壁进行隔热性能理论计算与仿真计算的对比,对隔热壁内部空气层的隔热性能进行分析。结论为:在车辆多层复合结构的隔热壁K值计算中,当空气层厚度大于一定厚度时,流体自然对流对隔热壁的隔热性能影响较大。利用多项式密度(Polynomial Denisity)和Boussinesq模型两种算法,对所得结论进行了验证。     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.