Robust and stable scheduling of a single machine with random machine breakdowns

For single-machine scheduling with random machine breakdowns, a new method considering both robustness and stability is proposed in this paper. The stability of the predictive schedule is measured by the sum of the absolute deviations between the planned job completion times and the realized ones. A surrogate measure is developed to evaluate the stability, assuming that there is only one breakdown. Generating a robust and stable schedule becomes a bi-objective optimization problem. A two-stage multi-population genetic algorithm is proposed to solve the bi-objective optimization problem. The method is applied to minimizing the total weighted tardiness of all jobs. The computational results show that the schedule generated by the proposed method is insensitive to disturbances, along with providing better robustness and stability.     

Robust stability and performance for interval process plants

In this paper, a two-degrees-of-freedom control design methodology for interval plants to guarantee both the robust stability and performance has been considered. A simple necessary condition and sufficient condition for robust Hurwitz stability of interval polynomial has been obtained using the results of Nie [Nie YY. A new class of criterion for the stability of the polynomials. Acta Mechnica Sinica 1976;110-6] for fixed polynomials. The proposed design methodology based on the obtained necessary condition and sufficient condition is then applied to design a robust control system for a second-order unstable plant in the presence of unknown but bounded parameter uncertainties. Subsequently, a pre-filter is constructed to ensure the desired system performance. Simulation results are used to establish the efficacy of the proposed method for interval plants.     

驾驶员对汽车行驶方向稳定性影响的分析方法

在驾驶员一汽车闭环系统操纵动力学模型基础上，将驾驶员参数变化范围用区间数表示，用直接优化法对非对称区间矩阵特征值问题进行求解，从系统与控制理论角度定量地揭示了驾驶员对汽车行驶方向稳定性的影响。分析结果表明，汽车行驶方向稳定性的区间分析方法可以应用于使车适合于人的汽车操纵动力学设计。     

基于遗传算法的冷连轧轧制规程优化设计

合理的轧制规程是使轧制过程达到最佳状态的重要保证。轧制规程涉及的有关数学模型和需要考虑的约束条件较多，因此其优化设计也较为复杂。应用遗传算法进行轧制规程优化设计，即以负荷均衡和板形良好为目标，在一定的约束条件下，对压下率分配比进行编码。通过遗传算子操作并保留每代优势个体，从而得到冷连轧轧制规程。对某1370冷连轧机进行设计比较，表明该方法优化速度快，适合在实际中应用。     

基于遗传算法的驾驶员-汽车闭环系统行驶方向稳定性研究

在驾驶员-汽车闭环系统操纵动力学模型基础上,将驾驶员模型参数变化范围用区间数表示,用遗传算法对非对称区间矩阵特征值问题进行求解,从系统与控制理论角度定量地揭示了驾驶员对汽车行驶方向稳定性的影响。分析结果表明:本文方法可以应用于“使车适合于人”的汽车操纵动力学设计。     

Scheduling of jobs and maintenance in a textile company

In this paper we consider a periodic maintenance scheduling problem in a textile company. In our research, a periodic maintenance schedule consists of several maintenance periods and each maintenance period is scheduled after a periodic time interval. The purpose of this paper is to find a schedule that minimizes the maximum tardiness subject to periodic maintenance and nonresumable jobs. An efficient heuristic is developed to provide the near optimal schedule for the problem. A branch-and-bound algorithm is also proposed to find the optimal schedule. Some important theorems associated with the problem are implemented in the algorithm. Computational results show that the proposed heuristic is highly accurate and efficient.     

超薄铝箔加工的动态集成排产方法

超薄铝箔的制造具有流程性生产、离散加工和装配生产的特征,根据其工艺路线特点,建立了基于极大极小代数法的数学模型,推导出状态变化的迭代公式,归纳了多目标的评价指数,用启发式方法将全部订单按照一定的规则进行优化排序,并产生炉次计划,使得订单能够及时交货,且降低了能耗。该排产方法集成了生产排序和装炉计划,能够在生产中随时动态地调整或增减计划的投入,在线控制生产。     

A Prototype Genetic Algorithm-Enhanced Multi-Objective Scheduler for Manufacturing Systems

This paper describes the development of a prototype genetic algorithm-enhanced multi-objective scheduler for manufacturing systems. A framework of the prototype scheduler is proposed which accepts data input from a database or file and outputs a near-optimal schedule. A scheduling toolbox with scheduling models for job shop, flow shop and cellular manufacturing, forms part of the prototype scheduler, and the schedule builder transforms the near-optimal solution into a valid shop floor schedule. The prototype system was validated for various cases, with and without constraints and multiple objective functions, (makespan and tardiness), enforced simultaneously with constraints. In the first case, the schedule generated was comparable to those obtained by other researchers. The prototype system was also tested for its ability to handle dynamic scheduling, e.g. a rush order. The results showed that all the job orders could be rescheduled within the original makespan, even though the order of one of the jobs was doubled.     

一种新调度类型及其在作业车间调度中的应用

研究改进遗传算法解决作业车间调度问题,问题染色体的编码采用基于工序的编码。针对传统的调度类型的局限性,提出全主动调度及其基于工序编码的产生机制。为了克服传统遗传算法求解调度问题易于早熟收敛的缺点,设计基于优先工序交叉(Precedence operation crossover,POX)和改进子代产生模式的遗传算法。用改进的遗传算法求解传统调度问题、交货期调度问题和提前/拖期(Earliness/Tardiness, E/T)调度问题,研究半主动、主动和全主动三种不同的调度解码机制对遗传算法提供解质量的影响。     

Robust stability analysis of fractional order interval polynomials

The paper deals with the robust stability analysis of a Fractional Order Interval Polynomial (FOIP) family. Some new results are presented for testing the Bounded Input Bounded Output (BIBO) stability of dynamical control systems whose characteristic polynomials are fractional order polynomials with interval uncertainty structure. It is shown that the Kharitonov theorem is not applicable for this type of polynomial. A procedure is given for computation of the value set of FOIP. Based on the value set, an algorithm is presented for testing the stability of FOIP. The results presented in the paper are useful for the analysis and design of Fractional Order Interval Control Systems (FOICS). Examples are given to show how the proposed method can be used to assess the effects of parametric variations on the stability in feedback loops with fractional order interval transfer functions.     

有限区间内设备顺序预防性维护策略研究

为了克服等周期维护模型忽略设备可靠性要求,以及长期运行期望维护周期模型忽略设备特定阶段维护需求的缺点,通过引入基于役龄递减因子和故障率递增因子的混合式故障率演化规则,建立了有限区间内基于设备可靠性的顺序预防性维护优化模型,并以威布尔分布为例,利用仿真方法对其进行了优化。仿真结果显示,该模型可使设备的维护周期呈递减之势,反映了设备在某一特定阶段的可靠性需求。     

单件小批量生产MRP算法改进及其应用

针对订单驱动的单件小批量生产模式，提出了一种“伸缩式”MRP改进算法，该算法继承了MRP的基本思想，根据物料清单将主生产计划分解成零部件的生产计划和原材料、采购件的采购计划，并在此基础上对MRP算法进行改进，根据交货期，利用“伸缩”提前期倒排和顺排计划，将生产计划排到工序级。经实例证明采用这种MRP算法，增加了车间排产的灵活性，提高了车间排产效率，生产按计划进行，有效地减少了订单拖延的情况。     

基于混合优化策略的自回归-滑动平均模型建模

自回归一滑动平均(ARMA)模型参数估计一直是ARMA模型建模问题的难点和重点,目前的模型参数估计方法都采用传统最小二乘法及其推广算法,预测精度低.采用基于混合优化策略的遗传模拟退火算法进行ARMA模型参数估计,克服了传统算法的缺点,并在此基础上利用遗传模拟退火算法可以确定ARMA阶次的特点,提出基于混合优化策略的ARMA模型建模方法.利用这种建模方法和传统建模方法对组合炮控系统精度进行建模比较,证明基于混合优化策略的ARMA模型建模方法收敛快,精度高.     

APPLYING PARTICLE SWARM OPTIMIZATION TO JOB-SHOPSCHEDULING PROBLEM

A new heuristic algorithm is proposed for the problem of finding the minimum makespan in the job-shop scheduling problem. The new algorithm is based on the principles of particle swarm optimization (PSO). PSO employs a collaborative population-based search, which is inspired by the social behavior of bird flocking. It combines local search (by self experience) and global search (by neighboring experience), possessing high search efficiency. Simulated annealing (SA) employs certain probability to avoid becoming trapped in a local optimum and the search process can be controlled by the cooling schedule. By reasonably combining these two different search algorithms, a general, fast and easily implemented hybrid optimization algorithm, named HPSO, is developed. The effectiveness and efficiency of the proposed PSO-based algorithm are demonstrated by applying it to some benchmark job-shop scheduling problems and comparing results with other algorithms in literature. Comparing results indicate that PSO-based a     

Phase retrieval based on coded splitting modulation

A new coded splitting imaging technique is proposed to reconstruct the complex amplitude of a light field iteratively using a single‐shot measurement. In this technique, a specially designed coded splitting plate is adopted to diffract the illuminating beam into multiple beams of different orders and code their wavefronts independently and differently. From the diffraction pattern array recorded on the detector plane, both the modulus and phase distributions of the illuminating beam can be reconstructed iteratively using known transmission functions of different orders of the coded splitting plate. The feasibility of the proposed technique is verified both numerically and experimentally.     

汽车主缸综合性能测试系统的开发

汽车主缸综合性能测试系统能对汽车主缸的残留阀、空行程、输出功能、排量、回程时间、密封性能以及耐压性能进行测试,可适用于现代各种汽车制动主缸的检测要求。测试结果表明,该试验台自动化程度较高,测量精度较高,数据分析及显示直观,测试性能稳定可靠,具有较好的应用和推广价值。     

Control of an electrostrictive actuator using Newton's method

Electrostrictive actuators are a class of smart transducers with a great potential for many submicron motion applications. A major challenge for the electrostrictive actuators exists in the control of such ultra-precision motions, which are often seriously influenced by the intrinsic behaviors of electrostrictive material like non-linearity, hysteresis and creep. Based on Newton's method, this paper presents a new iterative control algorithm to improve the positioning and tracking performances of a linear multilayer electrostrictive actuator. In this algorithm, the iterative gain is not fixed but variable according to the previous output feedback and the nominal input/output relationship of the electrostrictive actuator. The convergence of this algorithm is theoretically proved quadratic and experimentally verified correct. A comparison of effectiveness of the new algorithm with that of the conventional proportional integral (PI) control and gain-fixed iterative control algorithms is made. The results show that using this new iterative control algorithm both the stability and the speed of submicron motion control have been obviously improved for the tested electrostrictive actuator.     

网格任务调度算法的研究

提出了一种基于遗传算法和Min-Min的网格调度算法,该算法主要分为资源搜索和任务分配两部分。首先,利用遗传算法从网格的可用资源中快速地搜索出最优的或是近最优的资源;然后从任务队列中取一组任务,利用Min-Min算法把任务分配给已搜索到的资源上去执行。仿真实验结果证明:对于大规模资源的调度该算法是有效的,能够减少了任务执行时间,改善网格任务调度的效率。     

基于遗传算法的ARMA模型定阶新技术

针对时间序列分析与预测中最为常见的ARMA模型的定阶问题,在分析传统定阶方法缺点的基础上,提出了用遗传算法确定ARMA(n,m)模型的自回归阶数n和滑动平均阶数m的新方法。首先由ARMA模型的预测值与实测值定义平均相对变动值(Average relative variance,ARV),并根据其建立遗传算法的适应度函数;然后选取适当的种群数、交叉效、变异率及进化代数;通过逐代进化,得到最优的ARMA模型。最后,通过太阳黑子数据验证了基于遗传算法的ARMA模型定阶新技术的有效性和实用性。     

一种拉索套管外形的设计与优化

为了减小斜拉索的振动,延长其使用寿命,提出一种新的斜拉索套管外形。首先,采用空气动力学方法初步设计了一种斜拉索套管外形——仿水滴形;然后,通过对该外形与仿鱼雷外形的计算流体力学(computational fluid dynamics,简称CFD)模拟仿真结果进行分析比较可知,新外形能减小拉索尾部形成漩涡生成的概率,降低斜拉索产生的大幅振动,有效提高斜拉索的稳定性;最后,运用Matlab遗传算法对初始的仿水滴气动外形进行进一步的参数优化,得到优化后的仿水滴外形。优化结果表明,优化后新外形的临界最大压力值、速度值和阻力系数都有一定的减小,可以较好地降低斜拉索的振动。