基于解析解的GPS伪距量测定位趋近算法

用几何方法,给出了二维、三维测距定位问题解的解析表达式,在此解析解的基础上对GPS测码伪距定位问题提出一种趋近计算方法,并讨论了其收敛性,给出了其收敛的一个充分条件和解析求解中多解的裁决方法.     

水面舰艇编队对潜搜索效能评估模型

  目的  为提高搜索到目标潜艇的概率,更有效地开展水面舰艇编队搜潜行动,对舰艇应召搜潜路径规划问题进行研究。  方法  首先,构建基于隐式马尔科夫模型（HMM）框架的水面舰艇应召搜潜模型,设计两阶段启发式求解的方法,使搜潜命中概率期望值最大,利用进化算法（EA）,通过对种群内的个体进行交叉和变异操作,避免出现局部最优的问题,并与常规搜潜方法进行对比;然后,通过实验研究不同分割策略对路径优化的影响。  结果  单舰搜潜和多舰搜潜的仿真实验表明,采用所提方法能够获得最大化搜潜命中概率期望值以及最优搜潜路径。而分割次数的实验表明,合理的重新划分搜潜区域,有利于找到总体更优的搜潜路径。  结论  该模型能找到最优搜潜路径,有效提高水面舰艇编队搜潜效率。     

进港飞机调度的精华自适应遗传算法设计

对进港飞机进行合理调度，是空中交通流量管理的一个重要研究内容。基于精华自适应遗传算法，实现了单跑道降落飞机调度问题的求解，在不违反飞机间隔要求的情况下合理安排飞机的降落次序，给出各飞机经过优化的着陆时间，减少总的延误成本。仿真结果表明，所提出的方法计算效率高，实用可行，明显优于FCFS算法。     

内燃机曲轴轴心运动规律研究

采用修正的Holland方法对一台V型柴油机的各轴承轴心轨迹进行了多方案计算分析,包括改变平衡重大小,不同的轴承间隙和不同的机油黏度等计算工况。计算结果表明,影响变负荷轴承轴心运动轨迹的最主要因素是轴承载荷的合力方向,以轴承平面内某一半径射线为基准,在整个工作循环中轴承载荷方向变化在此射线两侧±90°范围内时,轴心运动稳定;超出这一范围则轴心运动轨迹不稳定;其他影响因素的微小变化会导致轴心运动轨迹的剧烈变化。     

基于启发式算法的并行多机调度问题研究

从车间生产调度的实际情况出发，针对最小化完工时间的多机调度问题，提出了一种改进的极大消去法，并利用该算法进行了调度仿真，仿真结果表明：该改进后的算法能够更好的解决大规模多机生产调度问题．     

Dynamic airspace sectorisation for flight-centric operations

Today’s air traffic operations follow the paradigm of ‘flow follows structure’, which already limits the operational efficiency and punctuality of current air traffic movements. Therefore, we introduce the dynamic airspace sectorisation and consequently change this paradigm to the more appropriate approach of ‘structure follows flow’. The dynamic airspace sectorisation allows an efficient allocation of scarce resources considering operational, economic and ecological constraints in both nominal and variable air traffic conditions. Our approach clusters traffic patterns and uses evolutionary algorithms for optimisation of the airspace, focusing on high capacity utilisation through flexible use of airspace, appropriate distribution of task load for air traffic controllers and fast adaptation to changed operational constraints. We thereby offer a solution for handling non-convex airspace boundaries and provide a proof of concept using current operational airspace structures and enabling a flight-centric air traffic management. We are confident that our developed dynamic airspace sectorisation significantly contributes to the challenges of future airspace by providing appropriate structures for future 4D aircraft trajectories taking into account various operational aspects of air traffic such as temporally restricted areas, limited capacities, zones of convective weather or urban air mobility. Dynamic sectorisation is a key enabling technology in the achievement of the ambitious goals of Single European Sky and Flightpath 2050 through a reduction in coordination efforts, efficient resource allocation, reduced aircraft emissions, fewer detours, and minimisation of air traffic delays.     

Dynamic change of aircraft seat condition for fast boarding

Aircraft boarding is a process mainly impacted by the boarding sequence, individual passenger behavior and the amount of hand luggage. Whereas these aspects are widely addressed in scientific research and considered in operational improvements, the influence of infrastructural changes is only focused upon in the context of future aircraft design. The paper provides a comprehensive analysis of the innovative approach of a Side-Slip Seat, which allows passengers to pass each other during boarding. The seat holds the potential to reduce the boarding time by approx. 20%, even considering operational constraints, such as passenger conformance to the proposed boarding strategy. A validated stochastic boarding model is extended to analyze the impact of the Side-Slip Seat. The implementation of such fundamental change inside the aircraft cabin demands for adapted boarding strategies, in order to cover all the benefits that accompany this new dynamic seating approach. To reasonably identify efficient strategies, an evolutionary algorithm is used to systematically optimize boarding sequences. As a result, the evolutionary algorithm depicts that operationally relevant boarding strategies implementing the Side-Slip Seat should differentiate between the left and the right side of the aisle, instead of the current operationally preferred boarding from the back to the front.     

自动事件检测算法的比较及评估

对现有的几种典型的高速公路事件自动检测算法的性能进行了评价,并给出各种算法的优缺点及比较评估标准,采用检测率(DR)和误报率(FAR)特征曲线及模拟退火算法进行了评价和优化,在比较、分析结果的基础上提出了智能检测算法的概念,并指出其今后的发展趋势。     

A hybrid heuristic strategy for liquefied natural gas inventory routing

As liquefied natural gas (LNG) steadily grows to be a common mode for commercializing natural gas, LNG supply chain optimization is becoming a key technology for gas companies to maintain competitiveness. This paper develops methods for improving the solutions for a previously stated form of an LNG inventory routing problem (LNG-IRP). Motivated by the poor performance of a Dantzig-Wolfe-based decomposition approach for exact solutions, we develop a suite of advanced heuristic techniques and propose a hybrid heuristic strategy aiming to achieve improved solutions in shorter computational time. The heuristics include two phases: the advanced construction phase is based on a rolling time algorithm and a greedy randomized adaptive search procedure (GRASP); and the solution improvement phase is a series of novel MIP-based neighborhood search techniques. The proposed algorithms are evaluated based on a set of realistic large-scale instances seen in recent literature. Extensive computational results indicate that the hybrid heuristic strategy is able to obtain optimal or near optimal feasible solutions substantially faster than commercial optimization software and also the previously proposed heuristic methods.     

Maximizing net benefits for conventional and flexible bus services

Transit ridership is usually sensitive to fares, travel times, waiting times, and access times, among other factors. Therefore, the elasticities of demand with respect to such factors should be considered in modeling bus transit services and must be considered when maximizing net benefits (i.e. “system welfare” = consumer surplus + producer surplus) rather just minimizing costs. In this paper welfare is maximized with elastic demand relations for both conventional (fixed route) and flexible-route services in systems with multiple dissimilar regions and periods. As maximum welfare formulations are usually too complex for exact solutions, they have only been used in a few studies focused on conventional transit services. This limitation is overcome here for both conventional and flexible transit services by using a Real Coded Genetic Algorithm to solve such mixed integer nonlinear welfare maximization problems with constraints on capacities and subsidies. The optimized variables include service type, zone sizes, headways and fares. We also determine the maximum welfare threshold between optimized conventional and flexible services) and explore the effects of subsidies. The proposed planning models should be useful in selecting the service type and optimizing other service characteristics based on local geographic characteristics and financial constraints.