An optimal data-splitting algorithm for aircraft scheduling on a single runway to maximize throughput

In this research, we present a data-splitting algorithm to optimally solve the aircraft sequencing problem (ASP) on a single runway under both segregated and mixed-mode of operation. This problem is formulated as a 0–1 mixed-integer program (MIP), taking into account several realistic constraints, including safety separation standards, wide time-windows, and constrained position shifting, with the objective of maximizing the total throughput. Varied scenarios of large scale realistic instances of this problem, which is NP-hard in general, are computationally difficult to solve with the direct use of commercial solver as well as existing state-of-the-art dynamic programming method. The design of the algorithm is based on a recently introduced data-splitting algorithm which uses the divide-and-conquer paradigm, wherein the given set of flights is divided into several disjoint subsets, each of which is optimized using 0–1 MIP while ensuring the optimality of the entire set. Computational results show that the difficult instances can be solved in real-time and the solution is efficient in comparison to the commercial solver and dynamic programming, using both sequential, as well as parallel, implementation of this pleasingly parallel algorithm.     

基于NFFD 算法的船体几何变形技术

本文以非均匀有理B样条基函数作为参数体属性,并结合非均匀控制点网格,建立了适用于船体几何的NFFD变形技术。重点阐述了NFFD方法的基本原理和变形规则,并以矩阵表示方法为基础构建了数学模型。研究了控制点数量和分布对变形结果的影响,增加了控制点变形几何的能力并获得了更大的设计空间。最后,以某CNG运输船为例完成了球鼻艏、船艏和船艉部分几何的自动变形。本文的工作为船型优化提供了良好的变形工具。     

Multi-criteria optimization of traffic signals: Mobility,safety, and environment

Two-dimensional multi-objective optimizations have been used for decades for the problems in traffic engineering although only few times so far in the optimization of signal timings. While the other engineering and science disciplines have utilized visualization of 3-dimensional Pareto fronts in the optimization studies, we have not seen many of those concepts applied to traffic signal optimization problems. To bridge the gap in the existing knowledge this study presents a methodology where 3-dimensional Pareto Fronts of signal timings, which are expressed through mobility, (surrogate) safety, and environmental factors, are optimized by use of an evolutionary algorithm. The study uses a segment of 5 signalized intersections in West Valley City, Utah, to test signal timings which provide a balance between mobility, safety and environment. In addition, a set of previous developed signal timing scenarios, including some of the Connected Vehicle technologies such as GLOSA, were conducted to evaluate the quality of the 3-dimensional Pareto front solutions. The results show success of 3-dimensinal Pareto fronts moving towards optimality. The resulting signal timing plans do not show large differences between themselves but all improve on the signal timings from the field, significantly. The commonly used optimization of standard single-objective functions shows robust solutions. The new set of Connected Vehicle technologies also shows promising benefits, especially in the area of reducing inter-vehicular friction. The resulting timing plans from two optimization sets (constrained and unconstrained) show that environmental and safe signal timings coincide but somewhat contradict mobility. Further research is needed to apply similar concepts on a variety of networks and traffic conditions before generalizing findings.     

汽车前照灯闪烁问题分析及设计优化

汽车前照灯是整车照明的重要组成,随着时代的发展,汽车前照灯的设计也越来越简单化、多样化。本文针对某车型项目阶段出现的前照灯闪烁问题,从前照灯的控制逻辑展开,分析故障产生的原因,并研究优化方案。     

基于粒子群算法的水下多元线阵阵形有源校正方法

针对存在阵元位置误差的水下多元线阵,提出一种基于粒子群优化算法的远场有源阵形校正方法.该方法选用2个辅助源分时工作方式,利用无条件最大似然方位估计算法构建目标函数,并通过粒子群算法对阵元位置进行寻优.利用该方法对均匀线阵进行性能仿真实验.结果表明:该方法稳健性好、校正精度高,具有一定的应用前景.     

基于OpenStreetMap的城市自行车网建模与多判据路径规划

自行车交通是一种健康、绿色、环保的交通出行方式,合理地规划自行车出行路线对于满足骑行者多元化出行需求、构建安全规范的城市交通出行环境具有重要的意义.在对真实骑行者路径选择行为深入分析的基础上,提出了基于Open Street Map的城市自行车网络的构建方法及基于其上的多判据自行车路径优化的数学模型,并给出了求解该模型的一种基于聚类的最优多判据路径规划方法.实验仿真结果表明,该模型及方法能够生成满足骑行者真实需求的多判据路线方案.     

Privacy-preserving MaaS fleet management

On-demand traffic fleet optimization requires operating Mobility as a Service (MaaS) companies such as Uber, Lyft to locally match the offer of available vehicles with their expected number of requests referred to as demand (as well as to take into account other constraints such as driver’s schedules and preferences). In the present article, we show that this problem can be encoded into a Constrained Integer Quadratic Program (CIQP) with block independent constraints that can then be relaxed in the form of a convex optimization program. We leverage this particular structure to yield a scalable distributed optimization algorithm corresponding to computing a gradient ascent in a dual space. This new framework does not require the drivers to share their availabilities with the operating company (as opposed to standard practice in today’s mobility as a service companies). The resulting parallel algorithm can run on a distributed smartphone based platform.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

横梁端部节点优化

通过有限元计算,对比几种常见的横梁端部连接方式,综合考虑结构整体强度、钢材使用量、舱室空间利用率、施工便利性等方面的影响因素,确定较优的连接过渡方式和过渡结构的参数尺寸,为船舶设计横梁端部节点形式的确定提供参考。