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针对柔性作业车间调度问题,考虑自动导引车(AGV)在车间制造过程中只参与装卸和搬运工作,提出一种实现AGV路径规划与柔性作业车间调度集成优化的融合调度模型。采用基于工序排序与机器选择两个子问题的二维向量编码方案,并在解码过程中提出基于最先服务原则的AGV安排策略。对鲸鱼优化算法进行离散化改进,针对性地设计了多种种群初始化策略,引入遗传算法的交叉、变异操作以提升鲸鱼优化算法的全局搜索能力,并嵌入局部搜索算法以达到全局搜索和局部搜索的平衡,构建了一种混合遗传鲸鱼优化算法(HGWOA)来求解该融合调度模型。通过经典测试算例验证了算法性能,并使用正交试验优化了算法参数。研究结果表明,HGWOA算法用于求解柔性作业车间AGV融合调度问题可以获得较好的效果。 相似文献
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具有柔性加工路径的作业车间批量调度优化研究 总被引:1,自引:0,他引:1
古典作业车间调度问题已经被研究了几十年并证明为 NP- hard问题。柔性作业车间调度是古典作业车间调度问题的扩展 ,它允许工序可以由一个机床集合中的多台机床完成加工 ,调度的目的是将工序分配给各机床 ,并对各机床上的工序进行排序以使完成所有工序的时间最小化。本文采用遗传算法进行柔性作业车间调度研究 ,针对柔性作业车间问题提出了一种新颖直观的基因编码方法以适用于批量调度 ,并分析了几种批量调度方案 ,最后给出了这些调度的仿真结果 ,证明单件最佳调度不适合扩展成批量最佳调度 相似文献
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Developing two multi-objective evolutionary algorithms for the multi-objective flexible job shop scheduling problem 总被引:1,自引:1,他引:0
Seyed Habib A. Rahmati M. Zandieh M. Yazdani 《The International Journal of Advanced Manufacturing Technology》2013,64(5-8):915-932
The aim of this paper is to study multi-objective flexible job shop scheduling problem (MOFJSP). Flexible job shop scheduling problem is a modified version of job shop scheduling problem (JSP) in which an operation is allowed to be processed by any machine from a given set of capable machines. The objectives that are considered in this study are makespan, critical machine work load, and total work load of machines. In the literature of the MOFJSP, since this problem is known as an NP-hard problem, most of the studies have developed metaheuristic algorithms to solve it. Most of them have integrated their objective functions and used an integrated single-objective metaheuristic algorithm though. In this study, two new version of multi-objective evolutionary algorithms including non-dominated sorting genetic algorithm and non-dominated ranking genetic algorithm are adapted for MOFJSP. These algorithms use new multi-objective Pareto-based modules instead of multi-criteria concepts to guide their process. Another contribution of this paper is introducing of famous metrics of the multi-objective evaluation to literature of the MOFJSP. A new measure is also proposed. Finally, through using numerous test problems, calculating a number of measures, performing different statistical tests, and plotting different types of figures, it is shown that proposed algorithms are at least as good as literature’s algorithm. 相似文献
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Peng Liu Xiaoye Zhou Lixin Tang 《The International Journal of Advanced Manufacturing Technology》2010,48(1-4):325-331
A new scheduling model in which both two-agent and position-dependent processing times exist simultaneously is considered in this paper. Two agents compete to perform their respective jobs on a common single machine, and each agent has his own criterion to optimize. The job position-dependent processing time is characterized by increasing or decreasing function dependent on the position of a job in the sequence. We introduce an aging effect and a learning effect into the two-agent single-machine scheduling, where the objective is to minimize the total completion time of the first agent with the restriction that the maximum cost of the second agent cannot exceed a given upper bound. We propose the optimal properties for the considered scheduling problems and then present the optimal polynomial time algorithms to solve the two scheduling problems, respectively. 相似文献
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Integrated and events-oriented job shop scheduling 总被引:1,自引:0,他引:1
Zeming Zou Congxin Li 《The International Journal of Advanced Manufacturing Technology》2006,29(5):551-556
When events such as rush orders or machine breakdown occurs during the production process in a job shop, the delivery date
of order may be delayed. To solve this problem, an events-oriented job shop scheduling process is built, and a scheduling
model integrated with an enterprise information system (EIS), including Enterprise Resource Planning (ERP), Product Data Management/Computer
Aided Process Planning (PDM/CAPP), etc., is proposed and analyzed in detail. A genetic algorithm and a hybrid allocation-based
method are used in scheduling. Lastly, an events-oriented job shop scheduling simulation system is presented . 相似文献
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Manish Kumar Sunil Rajotia 《The International Journal of Advanced Manufacturing Technology》2006,28(1-2):109-116
Today’s manufacturing systems are striving for an integrated manufacturing environment. To achieve truly computer-integrated
manufacturing systems (CIMS), the integration of process planning and production scheduling is essential. This paper proposes
a framework for integration of process planning with production scheduling in a job shop environment for axisymmetric components.
Based on the design specifications of incoming parts, feasible process plans are generated taking into account the real time
shop floor status and availability of machine tools. The scheduling strategy prioritizes the machine tools based on cost considerations. 相似文献
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多目标批量生产柔性作业车间优化调度 总被引:14,自引:0,他引:14
研究批量生产中以生产周期、最大提前/最大拖后时间、生产成本以及设备利用率指标(机床总负荷和机床最大负荷)为调度目标的柔性作业车间优化调度问题。提出批量生产优化调度策略,建立多目标优化调度模型,结合多种群粒子群搜索与遗传算法的优点提出具有倾向性粒子群搜索的多种群混合算法,以提高搜索效率和搜索质量。仿真结果表明,该模型及算法较目前国内外现有方法更为有效和合理。最后,从现实生产实际出发给出多目标批量生产柔性调度算例,结果可行,可对生产实践起到一定的指导作用。 相似文献
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Zeming Zou Congxin Li 《The International Journal of Advanced Manufacturing Technology》2006,29(5-6):551-556
When events such as rush orders or machine breakdown occurs during the production process in a job shop, the delivery date
of order may be delayed. To solve this problem, an events-oriented job shop scheduling process is built, and a scheduling
model integrated with an enterprise information system (EIS), including Enterprise Resource Planning (ERP), Product Data Management/Computer
Aided Process Planning (PDM/CAPP), etc., is proposed and analyzed in detail. A genetic algorithm and a hybrid allocation-based
method are used in scheduling. Lastly, an events-oriented job shop scheduling simulation system is presented. 相似文献
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Peng Liu Lixin Tang Xiaoye Zhou 《The International Journal of Advanced Manufacturing Technology》2010,47(5-8):657-664
This paper considers the two-agent scheduling problems with deteriorating jobs and group technology on a single machine, where the objective is to minimize the total completion time of the first agent with the restriction that the maximum cost of the second agent cannot exceed a given upper bound. Two agents compete to perform their respective jobs on a common single machine, and each agent has his own criterion to optimize. We introduce deteriorating jobs and group technology into the two-agent single-machine scheduling where the job processing times and group setup times are both functions of their starting times. There are two different linear deterioration functions. We propose the optimal properties and present the optimal polynomial time algorithms for two different scheduling problems, respectively. 相似文献
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P.Y. Gan K.S. Lee 《The International Journal of Advanced Manufacturing Technology》2002,20(3):214-222
Process planning and scheduling used to be two very separate processes. However, owing to the recognition of the intricate
relationship between them, recent work has focused on integrating the two processes. The use of flexible process plans in
scheduling allows more flexibility in production and thus gives substantial cost savings. It also increases the solution space
of the optimisation problem and makes it more critical to have an effective optimisation algorithm than for traditional scheduling
problems. This paper describes a process-planning and scheduling system that makes use of the branch and bound approach to
optimise priority weighted earliness of jobs scheduled in a mould manufacturing shop. Instead of consideing a flexible manufacturing
system, this paper focuses on the demands of less integrated factories, which are especially typical of mould manufacturing
shops. The layout of the system, the methodology of the algorithm and effectiveness of performance measures for real industrial
use are discussed in the paper. 相似文献
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Ferda C. Çetinkaya 《The International Journal of Advanced Manufacturing Technology》2006,29(1-2):178-183
The process of splitting a job lot comprised of several identical units into transfer batches (some portion of the lot), and
permitting the transfer of processed transfer batches to downstream machines, allows the operations of a job lot to be overlapped.
The essence of this idea is to increase the movement of work in the manufacturing environment. In this paper, the scheduling
of multiple job lots with unit sized transfer batches is studied for a two-machine flow-line cell in which a single transport
agent picks a completed unit from the first machine, delivers it to the second machine, and returns to the first machine.
A completed unit on the first machine blocks the machine if the transport agent is in transit. We examine this problem for
both unit dependent and independent setups on each machine, and propose an optimal solution procedure similar to Johnson’s
rule for solving the basic two-machine flowshop scheduling problem. 相似文献
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基于智能体技术,提出了芯片制造生产线动态调度新方法,实现了投料调度、工件调度与设备维护调度的集成。首先,给出了基于智能体的动态调度模型,该模型中包括管理智能体、投料智能体、工件智能体、设备智能体、运输智能体与人员智能体。投料智能体用于实现投料控制,工件调度通过工件智能体与设备智能体之间的协商实现,设备维护调度由设备智能体实现。通过智能体间的合作,能够实现投料控制、工件调度与设备维护调度的协同进行。然后给出了工件智能体与设备智能体问协商使用的协商协议(即带有时间约束的单步协商协议),以及智能体决策中使用的调度算法(包括投料调度算法,工件调度算法与设备维护调度算法)。最后,通过实例,给出了方法的使用过程,并进行了模拟仿真。仿真结果表明,集成的调度方法能更好地优化模型的生产率、加工周期与设备利用率,最终提高准时交货率。 相似文献
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针对工序加工时间不确定环境下的Job Shop调度问题,为了预估最差调度工况及其对应的调度性能指标边界,采用一类保守、稳健的Minimax分析方法,建立了基于提前/拖期惩罚成本的Minimax调度模型;为了解决传统基于遍历或枚举方法存在的搜索空间巨大的问题,提出并证明了给定调度顺序条件下,关于内层Max优化过程的凸函数定理,并依此定理提出了一种工序加工时间搜索空间过滤机制。针对Minimax调度问题存在的双空间寻优特性,在分析调度顺序种群和工序加工时间种群的交替进化机制的基础上,设计了一种高效的双空间协同遗传算法。最后通过仿真算例验证了该过滤机制和双空间协同遗传算法的有效性。 相似文献
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Gwo-Ji Sheen Lu-Wen Liao Cheng-Feng Lin 《The International Journal of Advanced Manufacturing Technology》2008,36(1-2):132-139
In reality, the machine might become unavailable due to machine breakdowns or various inevitable reasons, and machine might
have different capability to processing job. Motivated by this, we consider the problem of scheduling n non-preemptive and independent jobs on m identical machines incorporating machine availability and eligibility constraints while minimizing the maximum lateness.
Each machine is capable of processing at specific availability intervals. We develop a branch and bound algorithm applying
several immediate selection rules for solving this scheduling problem. 相似文献
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Jin Yulan Jiang Zuhua Hou Wenrui 《The International Journal of Advanced Manufacturing Technology》2008,39(9-10):954-964
Preventive maintenance (PM) planning and production scheduling are among the most important problems in the manufacturing industries. Researchers have begun to investigate the integrated optimization problem of PM and production scheduling with a single objective. However, many industries have trade-offs in their scheduling problems where multiple objectives must be considered in order to optimize the overall performance of the system. In this paper, five objectives, including minimizing maintenance cost, makespan, total weighted completion time of jobs, total weighted tardiness, and maximizing machine availability are simultaneously considered to optimize the integrated problem of PM and production scheduling introduced by Cassady and Kutanoglu. Multi-objective genetic algorithm (MOGA) is used to solve the integrated optimization problem. To illuminate the conflicting nature of the objective functions, decision-makers’ preferences of the multiple objectives are not integrated into the MOGA. The total weighted percent deviation, which represents not only the preferences of the objectives but also the deviations of the solutions, is proposed to help decision-makers select the best solution among the near-Pareto optimal solutions obtained by the MOGA. A numerical example reveals the necessity and significance of integrating optimization of PM and production scheduling considering multiple objectives. 相似文献
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针对纺织生产广泛存在的带工件释放时间、以最小化总拖期工件数和总拖期时间为目标的大规模并行机调度问题,提出一种基于工件聚类的遗传算法。该算法将求解过程分为工件聚类和工件排序两个阶段。在工件聚类阶段,基于影响并行机调度性能的重要调度特征量,采用改进的模糊C-均值聚类方法将所有待上机工件分为多个聚类;在工件排序阶段,采用基于规则编码的遗传算法,优化各聚类内工件的加工顺序。数值计算结果及实际应用效果表明,所提出的算法适用于求解带工件释放时间的大规模并行机调度问题。 相似文献
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Miguel A. Salido Joan Escamilla Adriana Giret Federico Barber 《The International Journal of Advanced Manufacturing Technology》2016,84(5-8):1303-1312
Many real-world scheduling problems are solved to obtain optimal solutions in term of processing time, cost, and quality as optimization objectives. Currently, energy-efficiency is also taken into consideration in these problems. However, this problem is NP-hard, so many search techniques are not able to obtain a solution in a reasonable time. In this paper, a genetic algorithm is developed to solve an extended version of the Job-shop Scheduling Problem in which machines can consume different amounts of energy to process tasks at different rates (speed scaling). This problem represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The evaluation section shows that a powerful commercial tool for solving scheduling problems was not able to solve large instances in a reasonable time, meanwhile our genetic algorithm was able to solve all instances with a good solution quality. 相似文献