网联车辆编队的鲁棒模型预测控制方法

为研究一类带有结构不确定干扰的网联车辆编队控制问题,考虑结构扰动服从盒式不确定集约束情况,提出一种基于鲁棒对等变换的模型预测编队控制方法。首先,基于车辆运动学状态方程,对传统车辆编队控制模型进行描述;其次,在状态方程中引入仿射结构不确定矩阵,构建最小最大化范式下的网联车辆编队控制模型;然后,在盒式不确定集下,基于鲁棒对等理论将该模型转化为计算上易于处理的上图优化模型;最后,采用序列二次规划算法获得最优编队控制方案,并通过仿真实验将该控制方案与传统车辆编队控制方案进行对比,以此验证模型的有效性。 结果表明：本文提出的最优编队控制方法能够抵御编队系统结构不确定干扰,在实现稳定编队目标的同时保障车辆的编队安全性。     

Engineering design optimization based on intelligent response surface methodology

An intelligent response surface methodology （IRSM） was proposed to achieve the most competitive metal forming products, in which artificial intelligence technologies are introduced into the optimization process. It is used as simple and inexpensive replacement for computationally expensive simulation model. In IRSM, the optimal design space can be reduced greatly without any prior information about function distribution. Also, by identifying the approximation error region, new design points can be supplemented correspondingly to improve the response surface model effectively. The procedure is iterated until the accuracy reaches the desired threshold value. Thus, the global optimization can be performed based on this substitute model. Finally, we present an optimization design example about roll forming of a ＂U＂ channel product.     

大型基础设施系统设计中的风险及概率

在大型基础设施系统中,不可避免地会出现重大的不确定性,因而,无法确保已建系统的安全性和可靠性.有功能失效甚至破坏的可能,同时也有相应的规避风险的措施.从实用角度出发,不确定性可以分为两大类:数据型(又称偶然型)不确定性和知识型(又称认知型)不确定性.前者可以通过对数据的观察来评估,而后者则需要主观判断.系统地分析了这两...     

Imprecise reliability assessment for heavy numerical control machine tools against small sample size problem

Small sample size problem is one of the main problems that heavy numerical control (NC) machine tools encounter in their reliability assessment. In order to deal with the small sample size problem, many indirect reliability data such as reliability data of similar products, expert opinion, and engineers’ experience are used in reliability assessment. However, the existing mathematical theories cannot simultaneously process the above reliability data of multiple types, and thus imprecise probability theory is introduced. Imprecise probability theory can simultaneously process multiple reliability data by quantifying multiple uncertainties (stochastic uncertainty, fuzzy uncertainty, epistemic uncertainty, etc.) together. Although imprecise probability theory has so many advantages, the existing natural extension models are complex and the computation result is imprecise. Therefore, they need some improvement for the better application of reliability engineering. This paper proposes an improved imprecise reliability assessment method by introducing empirical probability distributions to natural extension model, and the improved natural extension model is applied to the reliability assessment of heavy NC machine tool spindle to illustrate its effectiveness.     

价值工程在工程设计方案优选中的应用

建设项目投资控制贯穿于工程建设全过程,设计阶段是全过程投资控制的关键环节。在工程设计方案优选中引入价值工程理论,并指出价值工程分析的不确定性,应用灰色关联分析理论改进价值工程,使工程造价、使用成木及建筑产品功能匹配合理,有效降低建设投资。     

基于稳健优化的制造/再制造集成物流网络设计

为了合理设计制造／再制造集成物流网络，综合考虑网络中正向物流和逆向物流的设施集成与运输整合，以及新产品与再制造产品的需求量、可同收废旧产品数量和废旧产品可再制造率的不确定性，基于稳健优化方法建立了一种制造／再制造集成物流网络优化设计模型，据此确定网络中各种设施的数量、位置及物流量分配．算例结果表明，该模型能有效地解决不确定环境下的制造／再制造集成物流网络优化设计问题．     

Minimum resistance ship hull uncertainty optimization design based on simulation-based design method

In the ship hull optimization design based on simulation-based design (SBD) technology, low precision of the approximate model leads to an uncertainty form of optimization model. In order to enable the approximate model with finite precision to maximize the effectiveness, uncertainty optimization method is introduced here. Wave resistance coefficient approximation model, built by back propagation (BP) neural network, is represented as a form of interval. Afterwards, a minimum resistance optimization model is established with the design space constituted by principal dimensions and ship form coefficients. Double-level nested optimization architecture is proposed: for outer layer, improved particle swarm optimization (IPSO) algorithm with learning factor improvement strategy is used to generate design variables, and for inner layer, modified very fast simulated annealing (MVFSA) algorithm is used to solve the objective function interval with uncertainty region. Cases calculation proves the effectiveness and superiority of uncertainty optimization method for ship hull SBD optimization design, thus providing a good way for finding optimal designs.     

考虑行驶时间不确定性的合乘路径鲁棒优化方法

为应对实际合乘过程中时间不确定性带来的负面影响,本文研究不确定行驶时间下的合乘问题。采用预算不确定集合描述时间变量,引入不确定性水平可调节的预算系数,构建以车辆总里程最短和车辆数最少为目标的合乘路径鲁棒优化模型。并设计两阶段算法求解,第1阶段以两乘客间的可行合乘路径为基础,从车辆总里程节省率和乘客时间窗匹配灵活性两方面设计公式量化合乘匹配机会,以匹配机会为权重构建乘客图网络并聚类乘客需求;第2阶段设计以顺序插入启发式方法构造初始解的禁忌搜索算法求解。案例数据实验结果表明：本文聚类方法能保证优化质量并提高85%以上的计算效率,同时能缩减乘客等车时间和绕行距离;增大预算系数时解的鲁棒性逐渐提高,但会增加10%~40%的车辆数并降低1%~10%的里程节省率;大规模乘客案例和窄时间窗案例的合乘路径对不确定时间的敏感性更高,宽时间窗案例无需增加过多额外车辆和总里程就能达到较高水平的路径鲁棒性。     

优化计算中的可视化技术研究

自60年代以来,优化设计在工程设计领域获得了广泛应用,文中把可视化技术引入优化计算中,研究了优化计算中模型的可视化问题;对多维优化问题的研究,通过人机交互的手段（每次选择两个设计变量）,把优化模型投影到相应的子空间,通过图形动态显示寻优迭代过程,在一定程度上实现了对优化计算进行跟踪和驾驭,最后给出的算例证明了这一方法的可行性。     

Optimization of PERT Network and Compression of Time

In the traditional methods of program evaluation and review technique （PERT） network optimization and compression of time limit for project, the uncertainty of free time difference and total time difference were not considered as well as its time risk. The authors of this paper use the theory of dependent-chance programming to establish a new model about compression of time for project and multi-objective network optimization, which can overcome the shortages of traditional methods and realize the optimization of PERT network directly. By calculating an example with genetic algorithms, the following conclusions are drawn： （ 1 ） compression of time is restricted by cost ratio and completion probability of project; （2） activities with maximal standard difference of duration and minimal cost will be compressed in order of precedence; （3） there is no optimal solutions but noninferior solutions between chance and cost, and the most optimal node time depends on decision-maker＇s preference.     

发动机性能试验比油耗测量结果的不确定度分析

通过介绍测量不确定度的基本知识,对发动机性能试验中比油耗测量结果标准不确定度的影响因素、分量计算、不确定度的建模及其评定、数据处理方法作一介绍,有望为同类试验测量结果中不确定度评定方案的确定和后续处理提供参考。     

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针对航空公司安全系统风险评价中存在的不确定性因素，将证据理论引入航空公司安全系统的风险评价中，以解决评价过程中所遇到的不确定性问题，建立了航空公司安全系统风险评价指标体系，给出了基于证据理论的评价模型和算法，通过实例计算，验证了该方法能较好地解决航空公司安全系统风险评价过程中所遇到的不确定性问题。     

Application of Epistemic Utility Theory to Satisfactory Optimization

Satisficing control remains an important concept in decision making. In this paper, a new epistemic utility satisficing control theory is proposed for a new model of complex CMMO (constrained multi-objective multi degree-of-freedom optimization) system. As well, an epistemic utility function is developed and used to adjust the feasible region of soft constraints. The theory proved in this paper indicates that the utility function not only expresses the subjectivity of the original satisfactory-degree function, but also takes the cost of searching for a solution into account. Thus, the satisfactory-degree function can be adjusted and its rationality can be validated. This theory contributes an analytical method to the inverse satisfactory optimization problem. The findings indicate that this theory has good convergence and outcomes desired for satisfactory-degree functions.     

基于层次分析法的施工技术方案决策研究

在工程实践中往往会面临施工技术方案的选优决策问题,尤其是当方案评价指标性质不同,在定性和定量分析时不能简单地进行比较与评价。本文就小金山大桥浮式平台施工中的三种起吊系统的方案选优与决策问题,应用层次分析法基本决策理论,结合桥位处具体水文条件,通过建立模型进行层次分析和一致性检验,实现了最优选择。     

基于不确定性AHP和群决策理论的港口岸线等级评价模型

从政策法规、自然条件、经济、交通区位、配套服务等方面选取了影响港口岸线等级优劣的指标,引入了不确定性AHP和群决策理论来确定评价指标权重,使评价结果更具科学性和可信性。通过实证分析,将港口岸线分为3个等级,并提出了不同等级的开发使用意见,具有一定的推广和应用价值。     

双电机驱动双曲柄四环板式针摆行星传动研究

为了大幅度提高针摆行星减速器的承载能力，我们在国际上创新提出了多种结构型式的双曲柄环板式针摆行星减速器．结合其中一种主要的结构型式——双电机驱动双曲柄针摆行星减速器，介绍这种新型传动的工作原理、优点、结构设计、齿形优化设计及整机参数优化设计的理论与方法，并通过所优化设计的样机性能试验，来检验上述理论和方法的科学性．     

船舶主机选型的不确定性多属性决策方法

船舶主机选型需考虑各种技术与经济因素．满足基本技术要求的主机往往有多个，如何选择最理想主机，是一个不确定性多属性决策问题．文中针对一个实际例子加以说明，并提出了一种基于传统的多属性决策方法——逼近理想解的排序方法(TOPSIS)与证据结合准则相结合的方法来解决该问题．结果证明，该方法能合理解决这类问题．     

基于区间数距离的铁路线路方案决策模型与方法

为了研究铁路选线方案决策中定量指标与定性指标难以综合评价的系统量化问题,引入区间数理论,建立了基于区间数距离的铁路线路方案决策优化模型. 首先将选线方案中的定量和定性指标转化为区间数,得到区间数决策矩阵;然后对决策矩阵进行规范化处理得到规范化区间数决策矩阵;接着利用区间数距离法计算评价指标的权重,构造加权规范化决策矩阵;再基于加权规范化决策矩阵,利用区间数距离对决策方案排序择优,得出综合比选结果;最后结合工程比选实例验证了模型的作业程式. 结果研究表明:该模型在将含有不确定性信息的定性指标进行量化时,比传统的AHP方法可减少主观原因对决策结果的影响,尤其是指标权重的计算结果更可靠;在进行决策方案排序择优时比利用传统的投影法计算更为简便.      

Ship appearance optimal design on RCS reduction using response surface method and genetic algorithms

Radar cross section (RCS) reduction technologies are very important in survivability of the militarynaval vessels. Ship appearance shaping as an effective countermeasure of RCS reduction redirects the scatteredenergy from one angular region of interest in space to another region of little interest. To decrease the scatteringelectromagnetic signals from ship scientifically, optimization methods should be introduced in shaping design.Based on the assumption of the characteristic section design method, mathematical formulations for optimalshaping design were established. Because of the computation-intensive analysis and singularity in shapingoptimization, the response surface method (RSM) combined genetic algorithm (GA) was proposed. The poly-nomial response surface method was adopted in model approximation. Then genetic algorithms were employedto solve the surrogate optimization problem. By comparison RCS of the conventional and the optimal design,the superiority and effectiveness of proposed design methodology were verified.Ky words: radar cross section (RCS); characteristic section design method; response surface method; genetic algorithm (GA) was proposed. The polynomial response surface method was adopted in model approximation. Then genetic algorithms were employed to solve the surrogate optimization problem. By comparison RCS of the conventional and the optimal design, the superiority and effectiveness of proposed design methodology were verified.     

需求不确定下的网约车司机最优工资水平研究

在网约车出行系统中,乘客出行需求的不确定性会影响网约车平台制定合理的工资水平, 进而影响平台利润。本文研究出行需求不确定下的网约车司机工资水平。根据问题的数学描述,假设实际出行需求服从随机分布,司机数量供给服从劳动力供给理论,采用网约车研究领域广泛采纳的精准乘客-司机匹配函数描述乘客与司机间的匹配关系。在此基础上,建立求解网约车平台利润最大化的模型框架。案例研究发现：存在最优的工资水平,使得网约车平台利润最大化;最优工资水平、司机人数与乘客最大需求正相关,最优工资水平与平台影响力负相关;本模型给出期望利润最大化下的最优解,比平均值模型具有一定的鲁棒性,有效保障网约车平台利润。 结果表明,本文建立的最优工资水平模型可以有效研究需求不确定性下的网约车出行系统。