土坡三维最危险滑动面搜索方法

文章基于均质土坡旋转椭球形滑动面的假设,提出了一种用遗传算法确定均质土坡三维最危险滑动面及其对应的最小稳定系数的方法。该方法模拟了生物遗传进化的过程,克服了传统方法容易陷入局部极小值的缺点,是一种全局优化算法。     

A Bayesian approach for modeling origin-destination matrices

The majority of origin destination (OD) matrix estimation methods focus on situations where weak or partial information, derived from sample travel surveys, is available. Information derived from travel census studies, in contrast, covers the entire population of a specific study area of interest. In such cases where reliable historical data exist, statistical methodology may serve as a flexible alternative to traditional travel demand models by incorporating estimation of trip-generation, trip-attraction and trip-distribution in one model. In this research, a statistical Bayesian approach on OD matrix estimation is presented, where modeling of OD flows derived from census data, is related only to a set of general explanatory variables. A Poisson and a negative binomial model are formulated in detail, while emphasis is placed on the hierarchical Poisson-gamma structure of the latter. Problems related to the absence of closed-form expressions are bypassed with the use of a Markov Chain Monte Carlo method known as the Metropolis-Hastings algorithm. The methodology is tested on a realistic application area concerning the Belgian region of Flanders on the level of municipalities. Model comparison indicates that negative binomial likelihood is a more suitable distributional assumption than Poisson likelihood, due to the great degree of overdispersion present in OD flows. Finally, several predictive goodness-of-fit tests on the negative binomial model suggest a good overall fit to the data. In general, Bayesian methodology reduces the overall uncertainty of the estimates by delivering posterior distributions for the parameters of scientific interest as well as predictive distributions for future OD flows.     

Development of port service network in OBOR via capacity sharing: an idea from Zhejiang province in China

The ‘Silk Road Economic Belt and the 21st-Century Maritime Silk Road’ (One Belt One Road, OBOR) strategy initiated by the Chinese government has a significant impact on the business and logistics modes which involves Asia, Europe, Africa, and their adjacent seas. Many countries and ports are developing new strategies that are suitable for this economic environment. Compared with many ports in the world, the ports in Zhejiang province of China have a novel property. In addition to Ningbo-Zhoushan port, there are several other sea ports and river ports in that province. In this paper, we propose a concept of port service network that consists of a huge hub and multiple ports. Ports of small and medium sizes can share their capacities of different types of port service with the hub when the service capacities are integrated into the network. We develop a mixed integer nonlinear programming model to determine the optimal decisions in such a network with constraints on the budget to conduct integration. An optimization algorithm incorporated with a genetic algorithm is developed to solve large size problems. We provide managerial insights on the policies of government, including expanding port capacity, reducing fixed integration cost, and providing better financial condition.     

船体肋骨成型检测型线配准算法

船体肋骨数字化检测系统在进行船体肋骨完工检测时,需要进行肋骨型线测量点云与理论点云的数模配准。为改善配准效率和精度,提出一种船体肋骨型线配准算法,具体步骤包括点云粗配准、第一次ICP配准、测量点云偏置和第二次ICP配准。该算法已应用到船体肋骨成型数字化检测设备中,能够提升肋骨成型检测效率和精度,是实现船体构件加工成型智能制造的重要环节。     

Modeling and optimizing urban bus transit considering headway variation for cost and service reliability analysis

Due to the stochastic nature of traffic conditions and demand fluctuations, it is a challenging task for operators to maintain reliable services, and passengers often suffer from longer travel times. A failure to consider this issue while planning bus services may lead to undesirable results, such as higher costs and a deterioration in level of service. Considering headway variation at route stops, this paper develops a mathematical model to optimize bus stops and dispatching headways that minimize total cost, consisting of both user and operator costs. A Genetic Algorithm is applied to search for a cost-effective solution in a real-world case study of a bus transit system, which improves service reliability in terms of a reduced coefficient of variation of headway.     

A fuzzy logic-genetic algorithm approach to modelling public transport users’ risk-taking behaviour

This paper seeks to determine the effects of uncertainty in out-of-vehicle times on route choice. Data were collected at two key interchanges in Auckland, New Zealand. Previous work modelled the data using a manual approach to fuzzy logic. This study extends that work by automating the process through defining a black-box function to match the survey data, then employing a genetic algorithm to fine-tune the fuzzy logic model. Results show that automation and the genetic algorithm improve the model’s capability to more accurately predict ridership. The tuning of the membership functions is conducted twice, first using initial fuzzy rules and again after the fuzzy rules have been adjusted to reduce disparity between the output and survey data. The calibrated membership functions provided for operational (transfer waiting and walking time and delay) and physical attributes (safety and seat availability) can be used by practitioners to determine an estimated ridership.     

基于量子行为遗传算法的船体局部结构优化设计

采用遗传算法解决船舶复杂结构中混合设计变量优化问题时,其效果很有效,且能获得全局最优可行解。然而,简单遗传算法局部搜索能力差且易于早熟。为了提高对船舶复杂结构设计变量解空间的搜索能力,该文设计了一种基于二进制编码的适用于混合变量的量子行为遗传算法,比较适合于复杂函数的全局寻优,且搜索能力优于标准遗传算法。通过三个算例对算法的寻优能力进行测试,实验结果表明,采用量子行为遗传算法进行的船体局部结构优化设计具有较好的计算质量与计算效率。     

改进型PID算法在调距桨控制系统中的应用

调距桨控制系统在调整螺距时,为避免高工况时频繁调距和大幅度增减螺距指令带来的超调,提出改进型PID控制算法设计,并进行实船验证。应用结果表明,改进型PID算法可以有效的降低高工况的调距频率和抑制螺距指令剧变带来的控制系统超调。     

基于改进蚁群算法的交通分配研究

交通分配是交通规划诸多问题中被国内外学者研究得最深入、取得研究成果最多的内容。但是把蚁群算法应用到交通规划中在国内外都不多见。介绍蚁群算法在交通流分配中的应用。     

均匀设计和遗传操作并行的遗传算法

针对简单的遗传算法稳定性较差，容易发生早熟收敛的不足之处，提出了将均匀设计和遗传操作相结合的遗传算法，通过编码在问题的解空间和算法的搜索空间之间建立一个映射，对其进行交叉操作，变异操作和均匀设计操作，用典型的测试函数进行测试，证明了该算法是可行的，与单纯遗传算法相比，计算精度和收敛速度更高。