共查询到19条相似文献,搜索用时 640 毫秒
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针对最小化完工时间的等同和非等同并行多机调度一类问题,提出了一种递阶遗传算法。该算法根据问题的特点,采用一种递阶编码方案,此编码与调度方案一一对应。用递阶遗传算法优化并行多机调度不需设计专门的遗传算子,操作简单。计算结果表明,递阶遗传算法是有效的,能适用于大规模等同和非等同并行多机调度问题。 相似文献
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可重入生产系统的递阶增强型学习调度 总被引:2,自引:0,他引:2
对平均报酬型马氏决策过程,本文研究了一种递阶增强型学习算法;并将算法应用
于一个两台机器组成的闭环可重入生产系统,计算机仿真结果表明,调度结果优于熟知的两
种启发式调度策略. 相似文献
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针对已有的调度方法难以找到混杂柔性制造系统调度全局最优解的问题,根据一阶混杂Petri网模型提出了一种基于人工鱼群算法的混杂柔性制造系统调度方法.利用混杂Petri网不变行为状态序列与时间序列的对应关系把寻找最优解转换成寻找最优时间序列.首先给出了合法时间序列的定义及其基于人工鱼群算法的判定方法;然后给出了最优时间序列求解的人工鱼群算法,同时提出基于最优解视野变异的人工鱼群算法以解决多次优化过程中只会得到某个局部最优解的问题.最后基于这些算法给出混杂柔性制造系统的最优调度求解方法.实验结果表明所提出方法正确有效. 相似文献
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在生产调度领域,柔性作业车间调度问题是一个非常重要的优化问题。大多数研究通常优化的目标只是最大完工时间,而在实际中,往往要考虑多个目标。因此,提出了一种新的混合多目标算法用于解决柔性作业车间调度问题,其中考虑了3个目标,分别是:最大完工时间、机器总负载和瓶颈机器负荷。算法设计了有效的编码方式和遗传算子,并采用非支配近邻免疫算法求解非支配最优解。为了提高算法性能,提出了3种不同的局部搜索策略,并将其结合在多目标算法中。在多个数据集上的实验对比结果表明,所提算法优于其它代表性的算法。此外,实验结果还验证了局部搜索技术的有效性。 相似文献
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单机随机调度中机器的失效分析 总被引:4,自引:1,他引:3
随机调度问题已越来越受到人们的重视,单机随机调度的研究已经取得了不少结果,而
当机器失效时会出现什么现象呢?这是实际生产中更关心的问题.本文考虑了机器允许失效
时的单机随机调度问题,在部件的加工时间,机器的寿命和修复时间都服从指数分布的情况
下,得到并证明了使目标函数∑ωjCj,∑ωjUj,∑ωjTj最小的最优调度策略与机器是否失效
无关这一更具一般性的结论. 相似文献
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基于可变约束的多目标模糊柔性车间调度 总被引:1,自引:0,他引:1
在车间实际加工中,需要考虑:工件提交时间;加工不同的工序时,使机器处于就绪状态的调整时间及所产生的静态费用;机器加工时间及所产生的动态费用;原材料成本;工件交货期服从时间窗模糊分布;工件的某道工序有多台机器可供选择。针对这类车间调度,本文提出以极大化最小客户满意度和最小化工件原材料费用、静态费用和动态费用之和的两目标可变机器约束的模糊车间调度模型,给出基于改进编码和精英保留策略的进化算法,在此基础上对改进多目标进化算法解的合理性进行了简要的分析,以一个算例验证了算法的有效性,为多约束的模糊多目标调度提供了一种实现途径。 相似文献
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This paper is concerned with an asymptotic analysis of hierarchical production and setup scheduling in a stochastic manufacturing system consisting of a single failure-prone machine and facing constant demands for a number of products. At any given time the system can only produce one type of product, and the system requires a setup if production is to be switched from one type of product to another. A setup may involve setup time or setup cost or both. The objective of the problem is to minimize the total costs of setup, production, and surplus. The control variables are a sequence of setups and a production plan. An asymptotic analysis with respect to increasing rates of change in machine states gives rise to a deterministic limiting optimal control problem in which there is a control variable associated with each of the machine states and the production rate is obtained by weighting these controls with the stationary probabilities of the corresponding states. Asymptotic optimal controls for the original problem from optimal or near-optimal controls for the limiting problem are constructed 相似文献
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In this paper, we consider optimal production and setup scheduling in a failure-prone manufacturing system consisting of a single machine. The system can produce several types-of products, but at any given time it can only produce one type of product. A setup is required if production is to be switched from one type of product to another. The decision variables are a sequence of setups and a production plan. The objective of the problem is to minimize the cost of setup, production, and surplus. An approximate optimality condition is given together with a computational algorithm for solving the optimal control problem 相似文献
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A single production facility is dedicated to producing one product with completed units going directly into inventory. The unit production time is a random variable. The demand for the product is given by a Poisson process and is supplied directly from inventory when available, or is backordered until it is produced by the production facility. Relevant costs are a linear inventory holding cost, a linear backorder cost, and a fixed setup cost for initiating a production run. The objective is to find a control policy that minimizes the expected cost per time unit.The problem may be modeled as an M/G/1 queueing system, for which the optimal decision policy is a two-critical-number policy. Cost expressions are derived as functions of the policy parameters, and based on convexity properties of these cost expressions, an efficient search procedure is proposed for finding the optimal policy. Computational test results demonstrating the efficiency of the search procedure and the behavior of the optimal policy are presented. 相似文献
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Dong-Ping Song You-Xian Sun 《Automatic Control, IEEE Transactions on》1999,44(3):619-622
This paper considers an unreliable manufacturing system with random processing times and random product demands. The system can produce many part types and its total capacity is constrained by a fixed constant. The objective is to find an optimal service-rate allocation policy between different part types by minimizing the expected discounted inventory and backlog cost. Structural properties of the optimal control policy are investigated. It is shown that the optimal policy is of a switching structure. For producing a one part type case, the optimal control is a threshold policy. For producing a two part types case, the optimal control can be described by three monotone switching curves and its asymptote properties are derived. Numeric examples are given to illustrate the results 相似文献
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Abdolazim Houshyar 《Computers & Industrial Engineering》1991,21(1-4):447-451
A system of one machine used to produce m products in batches and a central storage used for storing raw materials and finished products is considered. The system maintains enough finished products to assure no stockout will happen. The machine has a finite production rate greater than or equal to the demand rate for each product, and thus operates with periodic start-ups and shut-downs. For special case when set-up for each product requires time and every product is produced in every cycle, the best policy given limited storage space is determined, and total production cost as a function of set-up costs, carrying cost, storage cost, and material handling cost is presented. A heuristic is developed that determines “optimal feasible cycle time” such that production scheduling remains feasible, the capacity of the central storage is not exceeded, and the overall costs are minimized. 相似文献
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《Computers & Operations Research》2001,28(11):1111-1130
The single-machine sequence-independent class setup scheduling problem is examined in this paper. It is assumed that jobs are classified into classes and a setup is required between jobs of different classes, but not of the same class. Furthermore, this setup time is fixed and depends only on the current job. Since the problem is NP-hard, a heuristic algorithm is proposed to find an approximate schedule that minimizes the maximum lateness on a set of jobs. The algorithm can easily be modified to solve the maximum tardiness problems as well. The accuracy of the heuristic algorithm in generating near optimal solutions is empirically evaluated.Scope and purposeFor batch manufacturing, it maybe desirable to produce many items of the same type, or class, at the same run in order to save the setup cost. However, committing facilities to long production runs for one product may inevitably make others tardy. Small batch size may conform urgent jobs to their delivery date, but one of the consequences would be the loss of productive efficiency due to numerous setups. Therefore, scheduling is basically a trade-off between the inherently conflicting efficiency measure and due-date compliance. This paper considers a single-machine scheduling problem in which jobs are classified into classes and a setup is required between jobs of different classes. The setup time is fixed and depends only on the current job. This problem is called a sequence-independent class setup problem and is NP-complete. 相似文献
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In this study, we investigate integrating the acquisition of input materials, material inspection and production planning, where type I and type II inspection errors are allowed, and the unit acquisition cost is dependent on the average quality level. This study aims to find an optimal purchase lot size (or here, equivalently, the fixed production rate multiplied by the production run time), input quality level and the associated inspection policy that minimize the total cost per item including the order cost, materials purchase cost, setup cost, inventory holding cost, and the quality-related cost. Furthermore, the boundaries, conditions and properties for the optimal production run time are obtained under an optimal inspection policy when the input material quality level is fixed. These findings will facilitate the establishing of an efficient algorithm for an optimal solution. The study demonstrates that a partial inspection approach could dominate over both the commonly used policies of full or no inspection, which is different from a previous report where the optimal inspection policy is either full or no inspection. A numerical example is performed to evaluate the impact of the two types of inspection errors and the process deterioration because of a nonconforming process input on the optimal solution, where a Weibull shift distribution is used to simulate the process failure time. Finally, conclusions are addressed. 相似文献