优化拉丁方试验设计方法及其应用

计算机仿真是复杂系统优化的一种有效手段,但需要耗费大量机时,必须严格限制仿真次数。针对此提出了优化拉丁方试验设计方法,该方法需要较少的仿真次数,且兼顾方案的正交性和均匀性,采用Cholesky分解生成初始解,通过模拟退火算法对拉丁方矩阵进行优化,定义动态权重因子实现正交性与均匀性的权衡。最后构建了一个实例,通过试验结果证明采用优化拉丁方试验设计方法可以生成具有较好性质的仿真方案,且仿真次数少。     

灵活的多层嵌套拉丁超立方体设计构造

计算机试验的设计方法越来越受到重视，嵌套拉丁超立方体设计是计算机试验设计中的一种新型方法，其在多种精度试验中有广泛的应用。但多数嵌套拉丁超立方体设计要求低精度试验次数需为高精度试验次数的倍数，这在应用中会有很大的局限性。通过对其构造方法的改进，得到一种结构更加灵活的多层嵌套拉丁超立方体设计，使得不同精度试验的次数可以更加灵活选取。该设计方法在一维投影上可以达到很好的均匀性。仿真结果表明，该方法较若干相关方法能够达到更小的均方误差。     

竞争失效产品恒应力加速寿命试验优化新方法

对加速寿命试验设计优化的相关知识进行研究分析,确定以竞争失效产品恒应力加速寿命试验为应用背景。在对加速寿命试验统计分析深入研究的基础上,通过分析方案要素、约束条件等建立优化目标函数,提出基于模拟退火算法的优化方法和具体实现思路。最后通过实例验证方法的可行性和实用性。     

序列近似优化方法及其在火箭外形快速设计中的应用

针对序列近似优化方法在代理模型构造与采样策略等方面的不足,基于采样点局部密度,引入与局部密度成反比的样本点影响体积概念,通过优化总影响体积确定径向基函数最优核宽度,满足序列近似优化过程不同规模、非均匀样本条件下的函数近似需要;建立潜在可行域最大距离加点准则,并与潜在最优加点准则结合平衡算法的探索能力与开发能力;建立三步收敛判定准则;构建改进序列近似优化的算法流程。对于Golinski减速器的优化设计问题,算法在目标函数调用42次后便搜索到全局最优解,体现了其良好的全局寻优能力与搜索效率。以"天航二号"火箭为例,建立其外形优化问题数学模型,所提优化方法在调用原始计算模型165次之后便搜索到全局最优解,大大提高了设计效率,同时飞行试验也表明设计结果满足要求。     

基于MOEA/D的柔性结构燃料—时间多目标优化控制研究

利用基于分解的多目标优化算法(MOEA/D)研究了柔性航天器多目标优化的rest-to-rest机动问题.基于空间飞行器刚柔耦合动力学方程,提出了最小时间-最少耗能的多目标优化控制模型;给出了基于MOEA/D的算法框架,并对柔性飞行器空间机动问题进行了多目标优化控制的分析设计;典型算例表明该算法可有效地应用于柔性航天器姿态机动控制器的分析设计之中.     

强化学习在多阶段装备组合规划问题中的应用

针对多阶段武器装备组合规划中的选择难、规划难问题,提出基于多目标优化算法以及强化学习技术的混合优化方法。在各个阶段以装备组合效能最大和成本最小为准则,构建单阶段多目标优化模型,并设计基于非支配排序遗传算法的求解算法以生成各阶段的Pareto解,在此基础上建立多阶段的组合优化模型。通过强化学习的Q-Learning方法,在各阶段的Pareto解中采用探索或者利用两种模式,生成各阶段的装备组合,并指导下一阶段的装备选型,从而生成整个周期内的规划方案。通过对比实验分析,验证了所提模型和算法的有效性,能够为多阶段武器装备组合规划提供辅助决策。     

基于粒子群算法的多基地雷达优化布站方法

为提高多基地雷达探测及"四抗"能力,提出了一种基于混沌变异粒子群算法的多基地雷达优化布站方法.定性分析了多基地雷达的布站原则,并对其量化,建立了优化布站的数学模型.为加快求解速度,结合混沌理论对标准粒子群算法进行了改进,给出了混沌变异粒子群算法在该优化问题中的设计方法,并与标准粒子群算法和遗传算法进行了仿真对比.结果表明,该方法能够快速有效得出多基地雷达优化布站方案.     

一种大扭矩制动器优化设计方法

为解决大惯量飞轮储能系统应急制动器优化设计的难题,提出了适用于多目标、多约束问题的改进粒子群算法。该算法利用加权算法将多目标优化问题转换为单目标优化问题,并通过罚函数方法将多约束问题转化为普通约束问题,再采用粒子群寻优算法进行求解。样机试验验证了大容量飞轮储能系统制动方案的可行性与摩擦制动器优化算法的优良性能。     

强冲击条件下铁路路基动态响应敏感度分析

研究列车在受到垂向冲击载荷时铁路路基的影响因素。基于拉丁超立方试验设计方法以及响应面(RSM)的建模方法,建立具有塑性应变损伤本构关系的铁路路基近似模型,并且对铁路路基动态位移响应因素的敏感度进行分析。结果表明:地基的弹性模量、基床以下路堤的弹性模量和道床的厚度为主要的影响因素,并且位移响应呈反比关系。     

协同反潜指控决策建模及优化研究

介绍了多目标优化模型.建立了协同反潜作战中目标威胁度和射击有利度模型,将遗传算法引入到指控决策优化过程中.设计了基于遗传算法的指控决策优化算法,并对算法作了适应度值乘幂变换和保存最优个体策略方面的改进.以编队协同防御为例,得到了未改进的遗传算法和改进的遗传算法的优化结果,并对两种方法的优化效果进行了比较,比较结果表明:无论是从算法的收敛速度还是寻优率方面,做过改进的算法都较未改进的算法优越.通过选择不同的初始种群进行多次试验的方法,验证了优化结果的正确性.     

Crane scheduling with spatial constraints

In this work, we examine port crane scheduling with spatial and separation constraints. Although common to most port operations, these constraints have not been previously studied. We assume that cranes cannot cross, there is a minimum distance between cranes and jobs cannot be done simultaneously. The objective is to find a crane‐to‐job matching which maximizes throughput under these constraints. We provide dynamic programming algorithms, a probabilistic tabu search, and a squeaky wheel optimization heuristic for solution. Experiments show the heuristics perform well compared with optimal solutions obtained by CPLEX for small scale instances where a squeaky wheel optimization with local search approach gives good results within short times. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Incremental approximation of optimal allocations

This paper concerns the approximation of optimal allocations by δ allocations. δ allocations are obtained by fixing an increment δ of effort and deciding at each step upon a single cell in which to allocate the entire increment. It is shown that δ allocations may be used as a simple method of approximating optimal allocations of effort resulting from constrained separable optimization problems involving a finite number of cells. The results are applied to find δ allocations (called δ plans) which approximate optimal search plans. δ plans have the property that as δ → 0, the mean time to find the target using a δ plan approaches the mean time when using the optimal plan. δ plans have the advantage that. they are easily computed and more easily realized in practice than optimal plans which tend to be difficult to calculate and to call for spreading impractically small amounts of effort over large areas.     

基于NSGA-II和多属性决策的防空火力分配

为了解决防空火力分配问题,首先运用NSGA-II算法求出Pareto最优解集,然后运用多属性决策方法对Pareto最优解集中的解进行综合评估,并从中找出一个最优解。用区间数定性描述各属性,建立了防空火力分配的三目标优化模型。描述了NSGA-II算法和多属性决策方法的运算步骤。在仿真算例中,得到了一个最佳防空火力分配方案,说明该方法对于防空火力分配问题有良好的应用价值。     

基于粒子群优化算法的空中目标定位

受干扰条件下,雷达难以对空中目标准确定位。针对这一问题,提出了当多基雷达接收站在空间随机分布时,利用粒子群优化算法解决根据到达时间差对空中目标定位中遇到的非线性最优化问题。所建算法首先初始化一个随机粒子群,然后根据适应度值更新粒子速度和位置,通过迭代搜索最佳坐标。仿真结果表明,在参数设定合理的情况下,该算法性能稳定,能找到逼近全局最优点的解。     

基于PSO算法的脉冲修正弹控制参数优化*

针对脉冲修正弹自身控制离散不连续特征,开展了脉冲修正弹脉冲控制参数优化设计方法研究。考虑到脉冲成本和精度的双重要求,选择以脉冲发动机工作次数和脱靶量最少为双目标函数,并在风干扰的条件下,提出了以脉冲控制时间间隔为离散脉冲控制参数设计变量建立优化模型,以此发展了一种改进型递减惯性权重粒子群优化脉冲控制参数的方法,提高了修正参数优化收敛速度。仿真结果表明,该算法能快速有效地获得最优解,为在干扰条件下寻找最优的脉冲修正参数和脉冲工作方式提供了一种优化设计思路。     

声自导鱼雷一次转角射击参数的优化

为了提高声自导鱼雷一次转角射击的发现概率,建立了一次转角射击的解析模型,并将射击参数的优化归结为一个带约束的优化问题。使用了一种改进的粒子群算法解决了上述问题,优化了自导扇面相遇点系数和出管直航距离两个射击参数。实验结果表明,使用优化后的射击参数显著提高了鱼雷的发现概率。     

作动器最优配置的柔性结构振动主动控制

柔性结构广泛应用于航空航天等领域,为了获得结构的最佳动力学性能,在主动振动控制中作动器或传感器位置优化成为关键。基于结构有限元动力学方程,在状态空间利用系统可控和可观Gramian矩阵考虑结构剩余模态的影响,推导一种新的作动器/传感器优化准则。根据优化准则结合非线性整数规划遗传算法对作动器的位置进行配置。以悬臂板为研究对象,采用基于状态反馈的线性二次型调节器研究悬臂板的振动控制效果。与其他配置方法进行比较,验证了新方法的优越性。     

Assortment optimization with position effects under the nested logit model

We study the assortment optimization problem with position effects under the nested logit model, whose goal is to find the revenue-maximizing subset of products as well as their corresponding display positions. In this joint assortment-position optimization problem, the choices of products are affected by not only their qualities and prices but also the positions where they are displayed. Despite determining the assortment and their corresponding display positions sequentially, we propose to solve this problem in an integrated way to obtain the optimal solution. We formulate this problem as a nonlinear binary integer programming model and develop a dynamic programming based solution approach to obtain the optimal assortment-position assignments. We carry out extensive numerical experiments to evaluate the benefit of our integrated approach. The most important insight we discover is that it is not necessarily better to put the most attractive products in the best position. Moreover, we show that compared to the sequential approaches, our approach can improve revenue by 10.38% on average, which suggests that firms should take into consideration position effects when making assortment decisions. Finally, we discuss results related to two extensions of this problem, that is, the special case when positions are preassigned to nests, and the joint assortment-position-price optimization problem.     

防空监视网络传感器资源分配的最优化

针对防空监视网络的传感器管理问题,讨论了传感器资源分配的最优化方法。提出了把传感器资源分配问题映射为多代理系统分布约束最优化问题的解决策略,设计了基于约束代价下界搜索的异步分枝定界最优化算法,实现了传感器资源分配问题最优解的异步并行搜索,给出的仿真实例说明了传感器资源分配最优化方法的有效性。     

Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

The increasing threat of explosions on the battle field and the terrorist action requires the development of more effective blast resistance materials and structures. Curved structure can support the external loads effectively by virtue of their spatial curvature. In review of the excellent energy absorption property of auxetic structure, employing auxetic structure as core material in curved sandwich shows the potential to improve the protection performance. In this study, a novel cylindrical sandwich panel with double arrow auxetic (DAA) core was designed and the numerical model was built by ABAQUS. Due to the complexity of the structure, systematic parameter study and optimal design are conducted. Two cases of optimal design were considered, case1 focuses on reducing the deflection and mass of the structure, while case2 focuses on reducing the deflection and increasing the energy absorption per unit mass. Parameter study and optimal design were conducted based on Latin Hypercube Sampling (LHD) method, artificial neural networks (ANN) metamodel and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The Pareto front was obtained and the cylindrical DAA structure performed much better than its equal solid panel in both blast resistance and energy absorption capacity. Optimization results can be used as a reference for different applications.