Autonomous sortie scheduling for carrier aircraft fleet under towing mode

Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.

A bi-population immune algorithm for weapon transportation support scheduling problem with pickup and delivery on aircraft carrier deck

The weapon transportation support scheduling problem on aircraft carrier deck is the key to restricting the sortie rate and combat capability of carrier-based aircraft.This paper studies the problem and presents a novel solution architecture.Taking the interference of the carrier-based aircraft deck layout on the weapon transportation route and precedence constraint into consideration,a mixed integer formulation is established to minimize the total objective,which is constituted of makespan,load variance and accumulative transfer time of support unit.Solution approach is developed for the model.Firstly,based on modeling the carrier aircraft parked on deck as convex obstacles,the path library of weapon transportation is constructed through visibility graph and Warshall-Floyd methods.We then propose a bi-population immune algorithm in which a population-based forward/backward scheduling technique,local search schemes and a chaotic catastrophe operator are embedded.Besides,the randomkey solution representation and serial scheduling generation scheme are adopted to conveniently obtain a better solution.The Taguchi method is additionally employed to determine key parameters of the algorithm.Finally,on a set of generated realistic instances,we demonstrate that the proposed algorithm outperforms all compared algorithms designed for similar optimization problems and can significantly improve the efficiency,and that the established model and the bi-population immune algorithm can effectively respond to the weapon support requirements of carrier-based aircraft under different sortie missions.

A Combined Arrival and Departure Scheduling for Multi-airport System

A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.

Gain-Scheduled Control and Stability Analysis of Morphing Aircraft in Transition Process

The large-scale morphing aircraft can change its shape dramatically to perform high flight performance.To ensure the transient stability of aircraft in the morphing process,a novel gain-scheduled control method is investigated numerically in this paper.Based on quasi-steady assumption,the linear parameter varying (LPV) model of the morphing vehicle is derived from its nonlinear equation.Afterwards,by solving a set of linear matrix inequalities along with the bound of the morphing rate via slowly varying system theory,the designed controller which considers the transition stability during the morphing process is obtained.Finally,the transition process simulations of the morphing aircraft are performed via the changes simultaneously in both span and sweep,and the results demonstrate the effectiveness of the proposed controller.

A Two-Stage Scenario-Based Robust Optimization Model and a Column-Row Generation Method for Integrated Aircraft Maintenance-Routing and Crew Rostering

Motivated by a critical issue of airline planning process,this paper addresses a new two-stage scenario-based robust optimization in operational airline planning to cope with uncertainty and possible flight disruptions.Following the route network scheme and generated flight timetables,aircraft maintenance routing and crew scheduling are critical factors in airline planning and operations cost management.This study considers the simultaneous assignment of aircraft fleet and crew to the scheduled flight while satisfying a set of operational constraints,rules,and regulations.Considering multiple locations for airline maintenance and crew bases,we solve the problem of integrated Aircraft Maintenance Routing and Crew Rostering(AMRCR)to achieve the minimum airline cost.One real challenge to the efficiency of the planning results is the possible disruptions in the initial scheduled flights.Due to the fact that disruption scenarios are expressed discretely with a specified probability,and we provide adjustable decisions under disruption to deal with this disruption risk,we provide a Two-Stage Scenario-Based Robust Optimization(TSRO)model.In this model,here-and-now or first-stage variables are the initial resource assignment.Furthermore,to adapt itself to different disruption scenarios,the model considers some adjustable variables,such as the decision to cancel the flight in case of disruption,as wait-and-see or second-stage variables.Considering the complexity of integrated models,and the scenario-based decomposable structure of the TRSO model to solve it with better computational performance,we apply the column and row generation(CRG)method that iteratively considers the disruption scenarios.The numerical results confirm the applicability of the proposed TSRO model in providing the AMRCR problem with an integrated and robust solution with an acceptable level of computational tractability.To evaluate the proposed TSRO model,which solves the AMRCR problem in an integrated and robust manner,five Key Performance Indicators(KPIs)like Number of delayed/canceled flights,Average delay time,and Average profit are taken into account.As key results driven by conducting a case study,we show the proposed TSRO model has substantially improved the solutions at all indicators compared with those of the sequential/non-integrated and nominal/non-robust models.The simulated instances used to assess the performance of the proposed model and CRG method reveal that both CPLEX and the CRG method exhibit comparable and nearly optimal performance for small-scale problems.However,for large-scale instances the proposed TSRO model falls short in terms of computational efficiency.Conversely,the proposed CRG method is capable of significantly reducing computational time and the optimality gap to an acceptable level.

基于物料延期干扰管理的飞机装配线动态调度

为了提升飞机装配过程中应对物料供应延期干扰的能力,对物料供应延期情况下飞机装配线动态调度问题进行研究。通过对物料交付确定性和预测性两类信息的分析将作业分为四类进行调度决策,建立了基于时间和事件混合驱动的周期性滚动调度框架和对应的数学优化模型。针对该问题设计了一种改进离散粒子群算法,将Levy飞行和离散化解码机制嵌入算法,滚动求解调度模型。数值实验结果表明,本文提出的调度方法能充分利用物料供应信息,在确定本阶段决策的同时前瞻性地进行预测决策,相比于其他动态调度方法,该方法能更有效地应对各类物料供应干扰,满足飞机装配动态调度的需求。

基于混合算法的飞机部件装配静态调度方法研究

飞机部件装配生产工艺流程复杂、生产周期长,如何制定高效的生产调度计划是急需解决的问题。分析了飞机部件装配的工艺流程,建立了飞机部件装配调度的约束条件,包括装配工序的先后约束和装配工装占用的约束,建立了飞机部件装配调度的目标函数,包括最小化拖期惩罚和最小化最大完工周期,对飞机部件装配调度问题进行了合理的假设和抽象,并建立了飞机部件装配调度模型。针对飞机部件装配静态调度问题,将粒子群算法和变邻域搜索算法进行了有效结合,设计了粒子群-变邻域搜索混合算法,并采用实例验证了该算法的有效性。

大规模飞机排班问题研究综述

飞机排班是航班计划的关键环节,直接影响民航运输的安全和经济效益。随着中国机队规模的稳步扩张,大规模飞机排班问题的研究愈发迫切;然而,早期基于连接网络或时空网络的机型指派模型及侧重运营收益、维修需求或鲁棒性的飞机排班问题模型,在问题规模、约束条件数量等方面往往受限,不能满足大规模飞机排班需求。本文在分析各类排班问题关联性和局限性的基础上,归纳了大规模一体化飞机排班问题的模型及其求解算法,分析了各算法的适用范围、优势和不足,并发现:分阶段排班模型无法保证全局最优解,一体化飞机排班模型更具有实际意义;精确算法理论上可保证求得最优解,但运算复杂、耗时长、模型分解难度大;启发式算法计算速度快,步骤简单,但无法保证求解的质量和算法的稳定性。在此基础上,进一步提出了未来大规模一体化飞机排班问题的研究方向:①问题建模方面,可在优化航线网络结构的同时,综合考虑航线需求、时间均衡调度和个性化机组指派等因素,建立一体化飞机排班集成模型,以解决现有模型的局限性;②问题求解方面,可以将Benders分解和列生成算法相结合,将整个问题分解为相对简单的主问题和子问题的组合,减少求解难度;也可将精确算法和启发式算法相结合,在保证求解精度的前提下尽量减少运算耗时,提高求解效率。

考虑不确定工期的飞机定检工序鲁棒优化模型

航空定检维修是确保飞机适航安全性重要工作,也是决定航空维修效率和成本关键环节。针对飞机定检维修工期受多种外部因素影响问题,建立考虑不确定工期的飞机定检调度模型。该模型以最大化工序鲁棒值为目标函数,同时考虑优先级约束和可更新资源约束。采用改进的萤火虫算法进行求解,将该算法应用到规模分别为10、20和30的标准实际案例验证。结果表明,相比于随机搜索算法,改进萤火虫算法得到的工序鲁棒值分别提高20.87%、93.41%和219.40%。最后对某维修中心PA44飞机的500 h定检维修案例进行分析。结果表明与实际情况相比,项目的鲁棒值提高了0.1182,证明了该模型在飞机定检工序鲁棒优化上有较好适用性。

民用飞机预测维修技术研究进展

民机维修理论伴随航空科技进步在不断往前发展,从定时翻修到以可靠性为中心的计划维修,以及先进的视情与预测维修理念。现代民机测试性的发展,特别是系统/结构健康监测技术的发展和成熟,丰富了现有的持续适航概念和方法体系,在确保飞机满足持续适航要求的前提下,飞机由经验化的基于时间的计划维修向更加高效的基于系统/结构实际健康状态的维修转变。本文总结了民用飞机预测维修技术的最新研究进展情况,从以传统计划维修模式为基础引出预测维修模式,包括结构/系统预测维修任务分析方法、预测维修方案优化、预测维修关键技术以及在民机领域的应用情况。

基于教与学优化的舰载机起飞出动动态调度

本文针对弹射器故障情形下的舰载机起飞出动调度,建立了舰载机起飞出动的多约束分布式流水线调度模型;结合基于扩展随机序解的编码和解码策略、动态调整策略,设计了基于教与学优化的舰载机起飞出动动态调度算法;最后,通过对仿真案例分析、故障预测精度对动态调度的影响分析,及动态调度算法的运行时间分析,结果验证了所设计的算法对舰载机起飞出动动态调度的可行性和有效性。

基于紧致子序列的航班着陆调度问题研究

航班着陆调度问题已被证明是NP难问题,综合考虑多种实际情况,建立了时间窗约束的航班着陆优化模型,定义了紧致子序列概念,论述了其性质及左移、分割和合并的条件。在此基础上,提出一种基于紧致子序列的算法(CSA)求解固定顺序下航班着陆调度问题。按照航班的最优着陆时间排序,运用CSA计算出该顺序下各航班着陆时间;采用循环线性交换和循环线性插空策略微调该固定顺序,不断迭代逼近模型的最优解;采用OR-Library数据集进行验证。实验结果表明,CSA结合启发式微调策略求解结果明显优于位移决策算法DALP和仿生算法(BA),与CPLEX、混合粒子群优化-局部搜索算法RH-HPSO-LS、细胞自动机优化(CAO)算法相近,在时间效率上明显优于对比算法;在小规模数据集上,计算精度与速度优势更加明显。CSA是一种确定性算法,不依赖于先验参数,具有更高的鲁棒性,保证了启发式微调策略不断逼近最优解。

舰载机弹药保障调度仿真系统

针对航空母舰飞行甲板上舰载机弹药保障面临的调度效率不高的问题,提出一种基于Unity3D的舰载机弹药调度三维虚拟演示方法,构建了面向航空母舰飞行甲板上舰载机弹药调度的三维虚拟仿真系统。通过定义系统,建立面向航空母舰舰载机弹药运输、装载调度过程的问题模型以及路径确定、顺序约束、装载位置补偿等处理规则,使用改进离散灰狼优化算法实现了调度过程优化求解。参照公开的场景信息搭建了航空母舰飞行甲板上舰载机弹药调度保障虚拟交互场景,设计了执行不同控制任务并能实现彼此之间交互控制的系统脚本,通过在系统虚拟场景实体模型上分别加载实现了虚拟场景的可控实时演示。对场景实例的优化求解与仿真演示验证了所提方法的有效性和可行性。

Optimization of fixed aviation support resource station configuration for aircraft carrier based on aircraft dispatch mission scheduling

Before the dispatch of the carrier-based aircraft,a series of pre-flight preparation operations need to be completed on the flight deck.Flight deck fixed aviation support resource station configuration has an important impact on operation efficiency and sortie rate.However,the resource station configuration is determined during the aircraft carrier design phase and is rarely modified as required,which may not be suitable for some pre-flight preparation missions.In order to solve the above defects,the joint optimization of flight deck resource station configuration and aircraft carrier pre-flight preparation scheduling is studied in this paper,which is formulated as a two-tier optimization decision-making framework.An improved variable neighborhood search algorithm with four original neighborhood structures is presented.Dispatch mission experiment and algorithm performance comparison experiment are carried out in the computational experiment section.The correlation between the pre-flight preparation time(makespan)and flight deck cabin occupancy percentage is given,and advantages of the proposed algorithm in solving the mathematical model are verified.

航线共享下转场训练计划集中编制多阶段方法

现阶段飞行航校的转场训练计划以各航校分散编排的模式为主,该模式下整体训练空域容量不能被充分利用。基于多航校转场航线资源共享理念,提出一种多航校联合转场训练计划集中编排问题的三阶段方法:第一阶段,建立多航校转场训练计划集中编制的转场训练路径优化模型;第二阶段,建立多航校转场训练计划集中编制的时刻优化模型;第三阶段,建立多航校通用教练机任务指派模型。以“3个飞行航校、8个转场点、18架教练机”规模问题进行算例分析,结果表明:与分散编排模式相比,集中编排下的转场训练路径编排成本降低了6.6%;训练计划结束时间与分散编排模式结果相当,但集中编排下的转场训练能够满足更多的训练需求数量;教练机任务指派方案的均衡性提高了10.1%。

飞机维修路径研究热点与前沿——基于CiteSpace的可视化分析

近年来,随着民航运输业的飞速发展,飞机维修路径规划研究越来越受到重视。为了探究飞机维修路径规划问题的研究现状、研究热点以及前沿趋势,以中国知网(CNKI)和Web of Science核心数据库2000年1月—2022年12月收录的国内外飞机维修路径规划研究的相关文献作为分析数据,将CiteSpace V软件作为辅助研究工具,分析飞机维修路径规划研究领域的研究人员、研究机构及其合作关系,结合知识图谱与文献内容总结该领域的研究热点与研究前沿。考虑国内的飞机维修路径规划研究情况,针对我国在该领域的研究趋势及重点研究内容提出研究建议,为今后飞机维修路径规划研究提供参考。

基于改进灰狼优化算法的舰载机着舰调度

针对第一类着舰模式下的舰载机着舰调度问题进行了研究,建立着舰调度模型,以最小化加权着舰延误时间和、着舰完成时间为优化目标,考虑舰载机战损程度、剩余燃油量的影响。为减轻人工调度的负担,提出一种改进灰狼优化(IGWO)算法对调度模型进行优化求解,在灰狼优化(GWO)算法的基础上,改进算法选择历史最优解灰狼个体为α狼,引入混沌算子,设置算法参数更新控制变量,以应对GWO算法后期收敛速度慢、可能陷入局部最优解的缺点。通过不同规模着舰调度案例仿真和算法对比,验证了IGWO算法的有效性,所提算法在30、60、90机规模着舰调度案例中的优化效果均优于对比算法,证明其具备一定工程应用价值。

基于HA算法的舰载机出动作业调度方法

出动离场是舰载机作战效能发挥的基础环节,本文研究其出动作业优化调度,将作业过程抽象为柔性车间调度问题,考虑优先序、资源及空间约束建立了混合整数规划模型,提出了一种基于种群进化搜索与邻域改进能力的混合遗传模拟退火算法,并给出了作业扰动时的重调度策略,通过引入任务表的生成构建了实际作业调度仿真架构。该架构融合了问题输入、动态扰动与算法,实用推广性强。仿真结果表明,所提算法收敛性快、解的准确性好、效率高,可有效解决任务表驱动下的出动调度问题;灵敏度分析发现,保障点军械加工对全局调度影响最为显著。

基于弹药挂载工作的舰载机保障作业调度

针对弹药挂载工作下舰载机保障作业问题,分析了弹药挂载作业与舰载机其他保障作业的约束关系,并基于保障资源约束,以舰载机保障作业完成时间和负载方差最小化为优化目标,建立了考虑弹药挂载工作下的保障作业调度模型。通过设计基于保障工序优先级的染色体片段编码方式,避免了大量不可行解的产生,提出了一种改进的NSGA-Ⅱ算法。以国外某型航母为例进行仿真分析,验证了模型与算法所得调度方案的可行性。

基于改进遗传算法的舰载机弹药挂载调度

舰载机弹药挂载工作是舰载机弹药保障中的一个重要环节,传统的舰载机弹药挂载调度通常忽略工作中存在的约束。针对该问题,分析了弹药挂载工作中存在的约束条件,以所有舰载机弹药挂载时间之和为优化目标,建立了考虑舰载机起始挂载时间不同和弹药挂载空间约束的舰载机弹药挂载调度模型,并提出了一种基于染色体片段编码的改进遗传算法,避免了大量不可行解的产生,提高了算法求解效率。仿真分析验证了所提模型与算法所得弹药挂载调度方案的可行性。