集成局部搜索策略的混合元模型优化方法在汽车轻量化设计中的应用

应用新近开发的基于混合元模型的优化方法(Hybrid and adaptive metamodeling method,HAM),对某款车的后车架系统进行轻量化分析。在保证后车架系统刚度的前提下,为进一步减小系统的质量,提高结果的精度,提出局部搜索策略。局部搜索策略使用元模型在设计空间内部构造的较小子空间内搜索,应用局部搜索策略的子空间是以HAM方法得到的样本点为中心上下偏移一定距离构成的。HAM将三种各具特点的元模型-克里金(Kriging)、径向基函数(Radial basis function,RBF)和二次多项式响应面(Fuadratic function,QF)有机结合,根据不同问题,自动选择最适合的元模型进行寻优。三种元模型能够在搜索过程中自适应地更新、重建,逐渐提高关注区域的精度。在使用HAM方法优化结束后,应用此策略在HAM方法得到的样本点构造的子空间内继续搜索来进一步提高结果的精度,减小系统的质量。在对后车架系统的轻量化设计中,局部搜索策略的应用,使此系统的质量在满足刚度要求下比仅使用HAM方法多减小了2.18 kg。     

A scatter search approach for general flowshop scheduling problem

This paper proposes a new evolutionary technique called scatter search for scheduling problems of a general flow-shop. Scatter search (SS) is applied to this problem as it is able to provide a wide exploration of the search space through intensification and diversification. In addition it has a unifying principle for joining solutions which exploit the adaptive memory principle to avoid generating or incorporating duplicate solutions at various stages of the problem. This methodology provides substantially better results than the Tabu search approach of Nowicki and Smutnicki (Manage Sci 42(6):797–813, 1996) and Jain and Meeran (Comput Oper Res 29:1873–1901, 2002). The proposed framework achieves an average deviation of 14.25% from the lower bound solution of benchmark problems of Demirkol et al. (Eur J Oper Res 109(1):137–141, 1998), while the scatter search technique gives the best solutions for 32 of 40 of their benchmark problems.     

求解柔性作业车间调度的遗传算法综述

柔性作业车间调度(FJSP)是一类具有广泛应用背景的调度问题,作为求解FJSP最受欢迎的算法之一,遗传算法引起了广泛关注。针对求解FJSP的遗传算法,特别是5类主要染色体编码方法以及相关的交叉和变异算子进行全面综述,并从编码可行性、编码空间与解空间的映射关系、染色体存储空间、解码复杂性、编码完备性、遗传操作复杂性和遗传操作多样性7个维度综合评价了5类编码方法。结果表明,MSOS-I编码是遗传算法求解FJSP较好的染色体编码方法,其染色体结构简单,并可选用较多类型的交叉和变异算子。     

基于混合遗传算法的混合装配线排序问题研究

为使混合装配线有效运作,研究了混合装配线的生产排序问题。以装配线上各种零部件消耗速率均匀化和最小生产循环周期最短为优化目标,描述了多目标排序问题,并建立了优化模型。针对基本遗传算法在求解排序问题时的早熟收敛问题,提出一种改进混合遗传算法。该算法借助模拟退火算法思想对适应度尺度进行调整,使遗传进化初期削弱种群中个体适应度差异,而在遗传进化后期强化种群中个体适应度差异,以提高对最优解的搜索能力。同时,根据个体适应度自动调整遗传操作参数,既保存了种群中的优良个体,又不失个体的多样性。最后通过案例分析验证了算法的有效性。     

Interior search algorithm (ISA): A novel approach for global optimization

This paper presents the interior search algorithm (ISA) as a novel method for solving optimization tasks. The proposed ISA is inspired by interior design and decoration. The algorithm is different from other metaheuristic algorithms and provides new insight for global optimization. The proposed method is verified using some benchmark mathematical and engineering problems commonly used in the area of optimization. ISA results are further compared with well-known optimization algorithms. The results show that the ISA is efficiently capable of solving optimization problems. The proposed algorithm can outperform the other well-known algorithms. Further, the proposed algorithm is very simple and it only has one parameter to tune.     

Hybrid inverse eigenmode problem for top-linked twin shear building models

A hybrid inverse eigenmode (HIE) problem is formulated such that a set of stiffnesses of a top-linked twin shear building model supported by a couple of prescribed shear-type systems at two interfaces is determined for a specified lowest eigenvalue of the combined system and a specified set of lowest-mode interstory-drift ratios in the upper stories. This model is equivalent to a fixed-fixed spring-mass model. Sufficient conditions are introduced and proved for a specified eigenvalue and a specified set of interstory-drift ratios in the upper stories to provide positive stiffnesses of the upper stories and to be those in the lowest eigenvibration. It is shown that, while there remains an indeterminacy of order one in the stiffnesses in a fully inverse eigenmode problem of a top-linked twin shear building model due to the existence of a compatibility condition, all the stiffnesses are determined uniquely in closed form in this HIE problem. A problem of eigenvalue analysis and its inverse problem are combined in this HIE formulation.     

基于混联机床立卧转换加工的机床运动控制算法研究

介绍了一种新型立卧转换式三杆混联机床—3-TPS混联机床,对该机床的结构进行了分析。文中给出了该机床在实现立卧转换加工时的坐标变换过程及变换方程,给出了实现立卧转换加工时的后置处理算法及数学模型,并分析了该机床在两种不同加工方式下所能够实现的三轴联动加工、四轴联动加工。文中所给的算法简单、直观、实用,方程为显示。     

Free-form型机床切齿优化(二)--混合进化遗传算法

针对Free -form型机床优化目标函数多维及非线性的特性 ,提出了一种混合进化遗传算法。该方法把遗传算法的全局搜索能力与参数线投影法的局部搜索能力结合起来。并在十进制为基因串的编码基础上 ,对遗传算子做了改进 ,使计算量减少 ,目标直观 ,优化性能显著提高。最后的例子也鲜明地表示出该优化方法的先进性。     

基于最小二乘支持向量机的发酵过程混合建模

提出了一种综合先验知识与最小二乘支持向量机的发酵过程建模方法，并且采用遗传算法进行最小二乘支持向量机的参数优化选取。该模型应用到一个具体发酵过程状态变量的预估中，仿真结果表明基于最小二乘支持向量机的混合模型具有很高的精度与范化能力，同时也表明了最小二乘支持向量机是软测量建模的一种有效方法。     

Hybrid Improved Self-adaptive Differential Evolution and Nelder-Mead Simplex Method for Solving Constrained Real-Parameters

In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.     

一种求解作业车间JIT调度问题的混合TS/MP算法

作业车间JIT调度属于一类典型的非正规性能指标调度问题,该类问题为每道工序设置了交货期约束,工序的提前或拖期完工均会产生相应的惩罚成本。采用禁忌搜索和数学规划相结合的混合调度方法进行求解。在算法的迭代搜索过程中,首先,由每个个体产生各机器上的工件加工序列,由此松弛了调度模型中的机器能力析取约束,然后,调用数学规划方法来优化各机器的空闲时间和各工序的开工时间。为提高禁忌搜索算法的计算效率,设计了一种包含交换和插入操作的邻域结构产生方案。最后,用JIT调度领域的32个标准测试算例验证了该调度算法的有效性。     

军用汽车混合电力驱动系统复合能源控制策略

电池技术是制约军用汽车混合电力驱动技术发展的关键因素之一.目前,广泛使用的各种单一储能源都难以满足军用汽车对能量和峰值功率的双重要求.采用复合能源结构,将高比功率能源与高比能量能源复合使用,能在现有的技术条件下,大大提高军用汽车能源系统的性能.为了充分发挥多种能源的优势,必须对复合能源功率分配进行合理控制.目前复合能源控制主要有加权法和滤波法,这两种方法各有侧重点,没有同时兼顾复合能源与发动机的特性.针对镍氢电池与超级电容的自身特性,提出一种加权控制和滤波器控制相结合的控制策略,首先细分复合能源控制模式,明确各个模式的切换条件,然后在具体的工作模式下采用滤波器控制,对复合能源输出功率进行分配.仿真分析和试验结果表明,超级电容起到了功率缓冲的作用,使得镍氢电池充放电过程得到了优化,避免了深充深放,复合能源的峰值功率大大提高.     

A GA-SA Multiobjective Hybrid Search Algorithm for Integrating Lot Sizing and Sequencing in Flow-Line Scheduling

It is very important that the sequencing and lot sizing in the flow-line environment are not independent. They should be integrated. In this paper, a multiobjective hybrid evolutionary search algorithm which combines a genetic algorithm and a simulated annealing algorithm is proposed and the performance of the proposed algorithm is compared with the existing genetic algorithm and the simulated annealing algorithm. The algorithms are coded independently and the performance is compared with randomly generated test problems. The objective functions considered for evaluation are the minimisation of makespan, minimisation of overtime and minimisation of holding cost. The scalar fitness function combining all the three objective functions, which minimises total cost, is used. The results are presented in tables and figures. The results show that the proposed hybrid algorithm performs better than the genetic algorithm and the simulated annealing algorithm.     

基于定向搜索算法的集装箱堆场翻箱问题

针对集装箱码头堆场翻箱问题,在以倒箱量最少为目标的基础上考虑集装箱场桥的移动代价,定义约束关系并建立了该问题的数学模型。提出最小基本倒箱量、最小场桥代价和最少倒箱次数三种搜索评价策略,并采用定向搜索算法进行求解。计算实例对比分析表明,所提出的启发式算法是有效的,能够为集装箱堆场翻箱问题提供决策依据。     

复杂情况下的三维集装箱装载问题混合算法

对复杂情况下的三维集装箱问题进行了描述,其约束主要包括重心位置约束、单箱重量约束、摆放方位约束、卸货顺序约束和集装箱型号和数量约束。基于禁忌规则,提出了求解该问题的模拟退火算法。设计了货物的摆放规则和序列生成方式,采用4种邻域,根据邻域的不同,构造了3种禁忌表,根据问题的特点,在模拟退火算法抽样过程中加入了禁忌规则。本文介绍了算法的原理,给出了具有代表性算例试验结果并且进行了分析。试验结果表明所提出的混合算法对复杂情况下的集装箱三维装载问题的有效性。     

配电架空电缆混合线路接地故障检定技术研究

配电网中的设备类型复杂、电路结构复杂、用户类型复杂。如果配电网出现故障后无法对故障进行即时的诊断和故障处理,会对配电网的安全、稳定、可靠运行造成影响,好多的故障源的定位查找还依赖于传统的人工手段。本文采用了一种兼具准确性和有效性的智能融合算法对配电网单相接地故障进行有效判定,该融合算法由瞬态HHT法、EMD法、瞬态能量法、首半波法根据不同情况下不同的权重占比构成。经过仿真环境下的模拟试验,基于智能融合算法的配电架空电缆混合线路的接地故障检定技术,可以有效解决架空电缆混合线路的单相接地故障的快速定位问题。     

Using genetic algorithms for the optimization of mechanisms

This work examines the possibility of using genetic algorithms for the optimization of the loads transmitted in mechanisms. The variables of design are the relative positions of the various connections, considered in a comparative manner. The minimization of the loads transmitted in the connections is achieved by optimizing the respective positions of those lead to less expensive solutions for bearings and sections of beams. The examples show that using this stochastic method is an efficient way to minimize loads in mechanisms.     

Study of key algorithms in topology optimization

The theory of topology optimization based on the solid isotropic material with penalization model (SIMP) method is thoroughly analyzed in this paper. In order to solve complicated topology optimization problems, a hybrid solution algorithm based on the method of moving asymptotes (MMA) approach and the globally convergent version of the method of moving asymptotes (GCMMA) approach is proposed. The numerical instability, which always leads to a non-manufacturing result in topology optimization, is analyzed, along with current methods to control it. To eliminate the numerical instability of topology results, a convolution integral factor method is introduced. Meanwhile, an iteration procedure based on the hybrid solution algorithm and a method to eliminate numerical instability are developed. The proposed algorithms are verified with illustrative examples. The effect and function of the hybrid solution algorithm and the convolution radius in optimization are also discussed.     

求解模糊作业车间调度问题的混合优化算法

针对模糊作业车间调度问题(Fuzzy job-shop scheduling problem, FJSSP),提出一种结合化学反应优化和禁忌搜索的混合算法(Chemical-reaction optimization and tabu search, CROTS),优化的目标是最小化最大模糊完工时间。算法采用基于工序的编码,通过扩展壁面碰撞、分子碰撞、合成、分解等操作算子,改进了基本化学反应优化(Chemical-reaction optimization, CRO)的四类基元反应。给出一种有效的交叉算子,并应用到分子碰撞、合成、分解三种基元反应中。对最好解进行禁忌搜索,进一步提高种群的搜索能力。结合16个经典算例试验分析,并与三种典型算法比较,验证算法具有较强的全局和局部搜索能力。通过18个随机算例的测试,验证算法具备求解较大规模问题的能力。     

A heuristic method for the combined location routing and inventory problem

The combined location routing and inventory problem (CLRIP) is used to allocate depots from several potential locations, to schedule vehicles’ routes to meet customers’ demands, and to determine the inventory policy based on the information of customers’ demands, in order to minimize the total system cost. Since finding the optimal solution(s) for this problem is a nonpolynomial (NP) problem, several heuristics for searching local optima have been proposed. However, the solutions for these heuristics are trapped in local optima. Global search heuristic methods, such as tabu search, simulated annealing method, etc., have been known for overcoming the combinatorial problems such as CLRIP, etc. In this paper, the CLRIP is decomposed into two subproblems: depot location-allocation problem, and routing and inventory problem. A heuristic method is proposed to find solutions for CLRIP. First of all, an initial solution for CLRIP is determined. Then a hybrid heuristic combining tabu search with simulated annealing sharing the same tabu list is used to improve the initial solution for each subproblem separately and alternatively. The proposed heuristic method is tested and evaluated via simulation. The results show the proposed heuristic method is better than the existing methods and global search heuristic methods in terms of average system cost.