Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm

Abstract

This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations.     

Optimization of Fare Structure and Service Frequency for Maximum Profitability of Transit Systems

Abstract

Providing efficient public transportation has been recognized as a potential way of alleviating congestion, improving mobility, mitigating air pollution, and reducing energy consumption. Many people use public transportation systems for their daily commute, while others use different transportation modes (e.g. cars, taxis, carpools, etc.). Inexpensive fares with good transit service encourages ridership, and the resulting revenue may be used to provide better service. Optimization of transit service frequency and its associated fare structure is desirable in order to increase revenue at reasonable transit operating expenditure. The objective of the study reported here is to maximize profit subject to service capacity constraint, while elastic demand is considered. The solution methodology is developed and applied to solve the profit maximization problem in a case study based on Newark, NJ, USA. Numerical results, including optimal solutions and sensitivity analyses, are presented. It is found that an optimal temporal headway and differential fare structure that maximizes total profit for the studied subway system can be efficiently solved.     

六宜路底面层沥青混合料组成优化设计分析

底面层是沥青路面结构层中承上启下的重要层位,文章结合六宜路沥青路面施工实例,以骨架密实型为目标对底面层沥青混合料配合比进行了优化设计分析,并通过室内试验与施工质量检测,验证了生产配合比优化后的沥青混合料的路用性能与施工质量。     

细集料组成对沥青混合料的密实性影响分析

针对目前骨架密实型沥青混合料优化设计的热点问题,文章结合工程实际,通过室内试验,分析了在形成沥青混合料骨架结构的基础上,细集料组成对沥青混合料密实性的影响,并提出了控制细集料各个筛孔的合理通过率,为骨架密实型沥青混合料级配优化设计提供参考。     

边坡治理方案优选的模糊多属性决策改进方法

由于边坡治理方案优选中的多层次、多目标、模糊性等特征给决策过程所带来的困难,提出了基于模糊多属性决策方法的边坡治理方案的改进评价体系;采用AHP与DEA的组合方法来确定了评价指标的权重,给出了边坡治理方案优选的一种改进的决策与评价模型,为边坡治理方案提供了一种更加合理可行的方法。并把该模型用于某公路边坡治理方案的优选过程中得到了较好的结果。     

区间非线性模糊法的沥青路面预养护决策

预防性养护方案选择属于多目标、多因素、多层次的复杂决策问题。在全面分析经济、技术、环境因素的基础上,综合运用专家打分法、区间层次分析法、模糊数学理论,建立了沥青路面预养护方案决策的区间非线性模糊决策方法。首先建立预养护非线性模糊决策模型,通过专家打分法确定评价指标属性值,根据区间判断矩阵得出各评价指标和影响因素的区间数权向量;对各指标进行层次非线性模糊分析,得出各预养护措施的隶属度,进而排序。以上海某公路为例,运用该方法对各预养护方案进行优选,结果表明该方法合理可行,为预防性养护方案决策提供了一种有效可行的方法。     

高速公路大修工程路面排水结构优化设计与施工

研究结合京港澳高速公路耒阳至宜章段大修工程实际情况,对沿线路面结构排水系统进行优化设计。研究表明采用有效耐久的路面排水系统,可有效地将已进入路面结构的水分尽快排出去,从而减少路面早期水损害产生,保障高速公路安全运行,研究结果可供同行参考。     

基于区间分析的发动机悬置系统稳健优化设计

针对不确定参数发动机悬置系统的优化问题,基于区间分析理论,将稳健设计与多目标优化相结合,提出一种提高发动机悬置系统隔振性能的稳健优化设计方法。该方法在区间数学模型的基础上建立悬置系统稳健优化模型,以动反力及其变化范围最小为目标函数,固有频率的合理配置为约束条件,悬置刚度为优化变量,并将悬置刚度和悬置位置的波动范围作为区间参数变量,对某型轿车发动机悬置系统进行稳健优化设计。结果表明,该方法改善了悬置系统的隔振性能,提高了系统参数的稳健性。     

多腔穿孔型宽频消声器声学特性的理论计算与优化

多腔穿孔型消声器可衰减涡轮增压发动机进气系统工作时产生的宽频噪声。本文根据将多腔消声器视为若干单腔消声元件串联而成的思路,结合单腔穿孔声阻抗模型,提出多腔消声器的声学计算方法,并以某多腔穿孔消声器为例,预测其传递损失。实验验证表明该计算方法在计算传递损失方面具有较高的精度。然后在此基础上,设定优化目标,选定3种不同优化变量的组合模式,采用非线性最小二乘法进行优化。结果表明,不同优化模式均可满足目标要求,可灵活地确定符合工程实际的最佳方案。所提出的方法可为增压发动机进气系统声学设计提供理论支撑和应用指导。     

交叉口混合交通流高维多目标信号优化控制

为提高我国城市道路交叉口混合交通流智能信号控制的效率,提出一种基于高维多目标进化算法的交叉口混合交通流信号智能优化控制方法.首先,提出一种新的高维多目标进化算法GRMODE,设计了新的算法模型并改进了Pareto支配排序等多项关键技术;其次,设计了基于GRMODE算法的交叉口混合交通流高维多目标信号优化控制模型,提供5项控制目标最优的信号控制方案.在南京市交叉口信号控制中的仿真实验结果表明,基于GRMODE算法的控制模型能够使交叉口机动车平均延误、停车次数、通行能力、非机动车平均延误及行人等待时间等多项性能指标同时达到最优,提升交叉口智能信号控制效率.