船舶汽轮机组优化设计研究

汽轮机组是船舶动力装置的重要组成部分,其重量和尺寸是影响船舶动力装置重量体积及布置的重要因素.建立包括汽轮机、冷凝器和齿轮减速器设计三部分的船舶汽轮机组数学模型,以汽轮机组重量最小为目标函数和在给定的约束条件下,采用不同的优化算法对机组进行了优化设计.与原方案相比,采用优化方案后汽轮机组重量明显减小,改进的自适应遗传算法有更好的优化性能,优化效果显著.     

Train rescheduling model with train delay and passenger impatience time in urban subway network

This paper considers the train rescheduling problem with train delay in urban subway network. With the objective of minimizing the negative effect of train delay to passengers, which is quantified with a weighted combination of travel time cost and the cost of giving up the planned trips, train rescheduling model is proposed to jointly synchronize both train delay operation constraints and passenger behavior choices. Space–time network is proposed to describe passenger schedule‐based path choices and obtain the shortest travel times. Impatience time is defined to describe the intolerance of passengers to train delay. By comparing the increased travel time due to train delay with the passenger impatience time, a binary variable is defined to represent whether the passenger will give up their planned trips or not. The proposed train rescheduling model is implemented using genetic algorithm, and the model effectiveness is further examined through numerical experiments of real‐world urban subway train timetabling test. Duration effects of the train delay to the optimization results are analyzed. Copyright © 2017 John Wiley & Sons, Ltd.     

Multi-objective re-synchronizing of bus timetable: Model,complexity and solution

This work is originally motived by the re-planning of a bus network timetable. The existing timetable with even headways for the network is generated using line by line timetabling approach without considering the interactions between lines. Decision-makers (i.e., schedulers) intend to synchronize vehicle timetable of lines at transfer nodes to facilitate passenger transfers while being concerned with the impacts of re-designed timetable on the regularity of existing timetable and the accustomed trip plans of passengers. Regarding this situation, we investigate a multi-objective re-synchronizing of bus timetable (MSBT) problem, which is characterized by headway-sensitive passenger demand, uneven headways, service regularity, flexible synchronization and involvement of existing bus timetable. A multi-objective optimization model for the MSBT is proposed to make a trade-off between the total number of passengers benefited by smooth transfers and the maximal deviation from the departure times of the existing timetable. By clarifying the mathematical properties and solution space of the model, we prove that the MSBT problem is NP-hard, and its Pareto-optimal front is non-convex. Therefore, we design a non-dominated sorting genetic (NSGA-II) based algorithm to solve this problem. Numerical experiments show that the designed algorithm, compared with enumeration method, can generate high-quality Pareto solutions within reasonable times. We also find that the timetable allowing larger flexibility of headways can obtain more and better Pareto-optimal solutions, which can provide decision-makers more choice.     

Flexible feeder transit route design to enhance service accessibility in urban area

To improve the accessibility of transit system in urban areas, this paper presents a flexible feeder transit routing model that can serve irregular‐shaped networks. By integrating the cost efficiency of fixed‐route transit system and the flexibility of demand responsive transit system, the proposed model is capable of letting operating feeder busses temporarily deviate from their current route so as to serve the reported demand locations. With an objective of minimizing total bus travel time, a new operational mode is then proposed to allow busses to serve passengers on both street sides. In addition, when multiple feeder busses are operating in the target service area, the proposed model can provide an optimal plan to locate the nearest one to response to the demands. A three‐stage solution algorithm is also developed to yield meta‐optimal solutions to the problem in a reasonable amount of time by transforming the problem into a traveling salesman problem. Numerical studies have demonstrated the effectiveness of the proposed model as well as the heuristic solution approach. Copyright © 2015 John Wiley & Sons, Ltd.     

Selection Method of Multi-Objective Problems Using Genetic Algorithm in Motion Plan of AUV

To research the effect of the selection method of multi-objects genetic algorithm problem on optimizing result, thismethod is analyzed theoretically and discussed by using an autonomous underwater vehicle(AUV) as an object. A changingweight vtlue method is put forward and a selection formula is modified. Some experiments were implemented on an AUV.TwinBurger. The results shows that this method is effective and feasible.     

战时潜艇阵地分配优化模型的研究

战时潜艇阵地分配问题受战争随机因素的影响。从机会约束规划入手，结合整数规划和目标规划，建立战时潜艇阵地分配优化模型，体现战时潜艇阵地分配的特点．结合问题的特殊性，设计出潜艇阵地分配优化模型的遗传算法，为解决快速收敛打下基础，符合战时决策的要求。     

基于RBF网络和遗传优化的船舶操纵模糊控制器

设计了一种基于RBF网络和遗传优化的船舶操纵模糊控制器。首先讨论了传统模糊控制器应用于船舶操纵控制的不足，然后根据模糊系统在特定情况下与RBF网络具有等价关系的特点，采用具有加权平均输出的RBF网络构造了一个船舶操纵模糊控制器，有效地消除了小偏差范围的舵角抖动现象。在此基础上，根据船舶操纵的特点提出了一种尺度变换因子的自整定方法，并采用遗传算法对自整定过程中的可变参数进行优化，以使控制器能够适应实时控制过程中的时变性和不确定性，保持良好的控制性能。最后针对某大型船舶的非线性模型，采用Matlab 6．1的Simulink工具进行了转艏操纵仿真试验，获得了满意结果。     

基于遗传算法优化的小波神经网络对船舶受扰力及力矩建模预报

首先构造小波神经网络,建立船舶横向和纵向运动模型及其运动受扰力模型,采用小波神经网络对船舶受扰力建模预报,并用遗传算法对其进行优化,对预报结果进行分析比较,给出超前5秒、15秒的船舶运动受扰力与力矩预报结果.     

随机响应约束下的桁架结构拓扑优化

研究随机响应约束下的桁架结构拓扑优化问题具有重要的工程应用前景.文章采用自适应遗传算法(AGA)求解了随机响应约束下的桁架结构拓扑优化问题.通过引入海明距离生成高质量的初始种群、采用自适应的交叉和变异算子以及对适应度函数进行线性标定这三个步骤改进了遗传算法的搜索效率以及收敛性.在拓扑优化列式中考虑杆件以及各自由度的拓扑变量以精确地模拟优化过程中杆件和结点的删除.建立了随机载荷作用下结构均方响应的表达式,并以此作为拓扑优化问题的约束条件.另外,提出了一些启发式算法来引导杆件和结点的删除.最后,通过对随机激励下的二维桁架以及三维桁架进行拓扑优化计算,证明了本文方法的实用性和有效性.     

土木工程结构健康监测研究进展

阐述了实施土木工程结构健康监测的必要性,介绍了结构健康监测系统的内涵、组成、监控内容、监控系统功能及其工程应用,讨论了结构损伤检测中的两类方法,重点对损伤识别中的动力指纹法、模型修正法、神经网络法、遗传算法进行了分析和比较,阐述了健康监测领域今后的主要研究问题和发展方向.