基于蚁群算法和群决策理论的动态路径优化研究

文章针对城市交通信号控制中的动态路径优化问题,综合考虑相邻交叉口间距和路段交通饱和度两个参数的影响,提出了一种基于蚁群算法和群决策理论的动态路径优化算法模型,并通过仿真实验,对比分析了该算法模型的有效性。     

液舱旋转射流惰化模拟及优化

为探究气体惰化机理,提高惰化过程效率,对卧式椭球状LNG液舱的气体惰化过程进行数值模拟与优化。采用从椭球状液舱端部直流射流、旋转射流和混合射流的进气方式,分析气体射流流场结构和惰化效果,探究不同进气方式对惰化过程影响的机理,并提炼其惰化优化方案。结果表明：在进气流量一定时,旋转射流的惰化效果优于直流射流和混合射流,这是由于旋转射流会产生更大的进气扩张角,可大幅减少惰化死角的存在,有利于在储罐内部形成推移式惰化;旋转射流相对直流射流可节省40.4%氮气量和惰化时间,相对混合射流可节省26.2%氮气量和惰化时间。旋转射流优化方案可减少氮气耗量并节省惰化时间,提高惰化过程效率,具有较高的经济性,对于实际LNG液舱的气体惰化过程具有重要指导意义。     

考虑实时浮态调整的散货船分舱优化

以某散货船为例,在船舶主尺度、船型参数和货舱总长度不变的情况下,将货舱间横舱壁的偏移距离作为优化参数,以船舶静水弯矩和静水剪力为目标函数进行优化,寻求使船舶静水载荷达到最小的横舱壁组合,并针对货物随着舱壁位置不同而引起的浮态变化,编写实时调整压载水的程序。该程序可应用在散货船的初步设计中,对船舶分舱设计和配载布置都具有指导性的意义。     

中压直流综合电力系统燃油经济性调度策略

由于研究对象、运行要求和调控手段存在差异,陆用电力系统和传统船用电力系统的燃油经济性策略无法直接应用到中压直流综合电力系统中。针对中压直流综合电力系统的能量优化调控需求,建立综合电力系统燃油经济性调度模型,提出基于分层优化方法的系统燃油经济性调度优化算法,实现对整流发电机组出力的优化。同时,提出适用于中压直流综合电力系统燃油经济性优化调度的方法,实现对发电机出力的优化调度,并通过仿真试验验证该方法的有效性。     

米勒循环结合可变涡轮增压优化柴油机性能的仿真与试验研究

在开发一款机车柴油机过程中,利用AVL BOOST软件对柴油机工作过程进行了仿真计算,计算了不同米勒强度和不同喷油正时条件下柴油机的性能参数。根据计算结果,排除了弱米勒的方案。针对强米勒和中米勒,开展了试验研究,通过调整喷油定时、增压压力设定、共轨喷射压力,进行了多方案试验研究,试验结果表明,强米勒方案虽然可以有效降低Nox排放,但是带来PM排放升高和涡轮前排气温度升高的问题,中米勒虽然降低Nox排放的效果弱于强米勒,但是能获得比较满意的PM排放,且涡轮前排气温度远低于强米勒,综合各方面性能参数的比较结果,在满足排放要求的前提下,中米勒为优选方案。     

基于气动效应的特长隧道断面优化探讨

铁路隧道净空面积的确定,不仅应考虑隧道建筑限界和机车车辆限界,还要考虑列车通过隧道时诱发的空气动力学效应。基于一维、可压缩、非定常的流动假设,推导得到车内瞬变压力、洞口微气压波和空气阻力计算公式,并结合这3个指标对现有城际铁路、高速铁路隧道设计规范进行论证和优化。结果表明： 针对大于10 km的特长隧道,在一定长度范围内,且在提高列车密封水平、增加洞口微气压波缓冲结构的情况下,可对特长隧道净空断面进行优化。     

固结黏土地层盾构直接破除排水板关键技术研究

宁波地铁5号线1期下穿高速公路路基时存在68°斜交长40 m的含塑料排水板的固结黏土地层,为研究盾构直接通过可行性、刀具选型、施工参数优化等问题,利用TBM掘进模态综合试验平台,进行了不同类型刀具、不同掘进参数的固结黏土地层排水板破除试验。研究表明： 对于含排水板的固结黏土地层,在合理选择刀具、盾构参数并优化掘进参数情况下,盾构法施工直接破除基本可行,试验为宁波地铁工程建设提供了依据,也可为类似工程设计及施工提供参考。     

Second best toll and capacity optimisation in networks: solution algorithm and policy implications

This paper looks at the first and second best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (Netw. Spat. Econ., 4(2): 161–179, 2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network.

Multi‐objective highway alignment optimization using a genetic algorithm

The available highway alignment optimization algorithms use the total cost as the objective function. This is a single objective optimization process. In this process, travel‐time, vehicle operation accident earthwork land acquisition and pavement construction costs are the basic components of the total cost. This single objective highway alignment optimization process has limited capability in handling the cost components separately. Moreover, this process cannot yield a set of alternative solutions from a single run. This paper presents a multi‐objective approach to overcome these shortcomings. Some of the cost components of highway alignments are conflicting in nature. Minimizing some of them will yield a straighter alignment; whereas, minimizing others would make the alignment circuitous. Therefore, the goal of the multiobjective optimization approach is to handle the trade‐off amongst the highway alignment design objectives and present a set of near optimal solutions. The highway alignment objectives, i.e., cost functions, are not continuous in nature. Hence, a special genetic algorithm based multi‐objective optimization algorithm is suggested The proposed methodology is demonstrated via a case study at the end.     

船舶六自由度转台电液伺服系统参数整定方法

针对船舶六自由度转台电液伺服系统的参数整定问题,提出一种基于多目标遗传算法和多属性决策的PID参数设计方法,综合考虑了系统超调量、稳定时间和ITAE指标,采用多目标遗传算法求出Pareto最优解。使用客观赋权的信息熵法对最优解的属性进行权值计算,然后采用逼近理想解的排序方法（TOP—SIS）进行多属性决策（MADM）研究。计算了转台电液伺服控制的数值算例,结果表明本文提出的联合方法通用性好,所设计的PID性能优异,适合工程实际应用。