共查询到19条相似文献,搜索用时 109 毫秒
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针对间歇生产过程柔性操作和动态变化的特征 ,提出综合应用基于知识的调度算法和多代理技术实现间歇生产过程智能调度的方法 ,建立间歇过程智能调度的结构模型 ,并以一间歇过程示例的仿真研究说明所提出方法的思路和可行性 相似文献
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建立有效的间歇生产调度模型一直是生产调度问题研究的热点,基于特定事件点的连续时间建模方法是优化短期间歇生产调度问题的有效工具。基于状态设备网络和特定事件点概念,建立非线性的连续时间间歇生产调度模型。为了解决非线性引起的求解困难,该模型使用替代方法线性化模型中的双线性项,替代法不仅将建立的混合整数非线性规划模型转化为混合整数线性规划模型,且由于其不包含大M松弛项,能使模型搜索空间更紧凑,模型求解效率更高。通过3个实例对比实验表明了基于状态设备网络描述的改进间歇生产调度模型搜索高效性。另外,模型中还给出了不同存储条件下,基于状态设备网络描述的间歇生产调度模型约束,扩展了模型适用性。 相似文献
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为了建立间歇工业过程的优化调度策略,研究了采用TPN(赋时Petri网)建立其生产调度模型的方法,并提出了基于GA(遗传算法)对此TPN调度模型进行优化的技术。论文引入了一个青霉素发酵间歇过程的仿真平台,以此为实例对象,讨论了TPN调度建模及GA优化的具体步骤,给出了满意的优化调度计算结果。 相似文献
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ZW多产品间歇过程调度及在线调整 总被引:1,自引:1,他引:1
针对多产品间歇过程调度提出了分层递阶的Petri网建模方法,利用赋时Petri和Petri网的简化技术描述不同层次的生产问题,具有很强的模型描述能力。另外,在调度决策层可以方便地集成优化策略和在线调整算法,使问题求解更加灵活。 相似文献
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不确定条件下的间歇生产调度优化是生产调度问题研究中具有挑战性的课题。提出了一种基于混合整数线性规划(MILP)的鲁棒优化模型,来优化不确定条件下的生产调度决策。考虑到生产过程中的操作成本和原料成本,建立了以净利润最大为调度目标的确定性数学模型。然后考虑需求、处理时间、市场价格三种不确定因素,建立可调整保守程度的鲁棒优化模型并转换成鲁棒对应模型。实例结果表明,鲁棒优化的间歇生产调度模型较确定性模型利润减少,但生产任务数量增加,设备空闲时间缩短,从而增强了调度方案的可靠性,实现了不确定条件下生产操作性和经济性的综合优化。 相似文献
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建立有效的间歇生产调度模型一直是生产调度问题研究的热点,基于特定事件点的连续时间建模方法是优化短期间歇生产调度问题的有效工具。基于状态设备网络和特定事件点概念,建立非线性的连续时间间歇生产调度模型。为了解决非线性引起的求解困难,该模型使用替代方法线性化模型中的双线性项,替代法不仅将建立的混合整数非线性规划模型转化为混合整数线性规划模型,且由于其不包含大M松弛项,能使模型搜索空间更紧凑,模型求解效率更高。通过3个实例对比实验表明了基于状态设备网络描述的改进间歇生产调度模型搜索高效性。另外,模型中还给出了不同存储条件下,基于状态设备网络描述的间歇生产调度模型约束,扩展了模型适用性。 相似文献
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油田GPS车辆调度系统是为胜利油田开发的基于GPS定位技术的车辆调度系统,该系统主要基于移动通信网络运行的,其中涉及多种车载终端控制模式,本文主要是通过,对比分析各种车载终端控制模式在该系统中的实现方法、技术要点、适用范围及优缺点等方面内容,结合新的需求的提出一种新的分布式车载终端控制模式思路、实现方案、实验方法等一系列的问题,通过本文的描述,进一步优化和改进油田GPS车辆调度系统中车载终端控制模式,使其更加高效、健壮、稳定,更好为本系统及油田的安全生产服务。 相似文献
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具有零等待的flow shop问题的免疫调度算法 总被引:1,自引:1,他引:0
针对间歇过程中存在的具有零等待的flowshop调度问题,建立了相应的数学模型,并结合免疫算法的特点,提出一种新的解决此类问题的免疫调度算法。通过仿真试验,证明了算法的有效性。 相似文献
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In this work, the mixed integer linear programming (MILP) model developed in Orçun et. al 1996 for optimal planning and scheduling of batch process plants under uncertain operating conditions is further improved to deal also with discrete probability functions. Furthermore, the logic behind integrating the processing uncertainties within the MILP model is implemented on the variations in the production volumes that can be faced in some batch processes such as Baker's yeast production. The modified model is tested on Baker's yeast production plant data to illustrate the effect of uncertainties on the production planning and scheduling. The results show that the plant production will be improved by 20% when the optimal production planning and scheduling is utilized by fine tuning the degree of risk the management can resist. An example on how a process design engineer may utilize such an MILP model for optimal planning and scheduling of batch process plant and identify plant problems, such as the bottleneck operations, is also included. A simulation type analysis on how to improve the processing site, i.e. the effect of introducing an extra operator to the bottleneck operation, is also demonstrated in this work using the available plant data. 相似文献
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《Computers & Chemical Engineering》2001,25(4-6):627-634
The main objective of this paper is to develop an integrated approach to coordinate short-term scheduling of multi-product blending facilities with nonlinear recipe optimization. The proposed strategy is based on a hierarchical concept consisting of three business levels: Long-range planning, short-term scheduling and process control. Long-range planning is accomplished by solving a large-scale nonlinear recipe optimization problem (multi-blend problem). Resulting blending recipes and production volumes are provided as goals for the scheduling level. The scheduling problem is formulated as a mixed-integer linear program derived from a resource-task network representation. The scheduling model permits recipe changeovers in order to utilize an additional degree of freedom for optimization. By interpreting the solution of the scheduling problem, new constraints can be imposed on the previous multi-blend problem. Thus bottlenecks arising during scheduling are considered already on the topmost long-range planning level. Based on the outlined approach a commercial software system has been designed to optimize the operation of in-line blending and batch blending processes. The application of the strategy and software is demonstrated by a detailed case study. 相似文献
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We propose a novel method for integrating planning and scheduling problems under production uncertainties. The integrated problem is formulated into a bi-level program. The planning problem is solved in the upper level, while the scheduling problems in the planning periods are solved under uncertainties in the lower level. The planning and scheduling problems are linked via service level constraints. To solve the integrated problem, a hybrid method is developed, which iterates between a mixed-integer linear programming solver for the planning problem and an agent-based reactive scheduling method. If the service level constraints are not met, a cutting plane constraint is generated by the agent-based scheduling method and appended to the planning problem which is solved to determine new production quantities. The hybrid method returns an optimality gap for validating the solution quality. The proposed method is demonstrated by two complicated problems which are solved efficiently with small gaps less than 1%. 相似文献
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In the past two decades, short-term scheduling of multipurpose batch plants has received significant attention. Most scheduling problems are modeled using either state-task-network or resource-task-network (RTN) process representation. In this paper, an improved mixed integer linear programming model for short-term scheduling of multipurpose batch plants under maximization of profit is proposed based on RTN representation and unit-specific events. To solve the model, a hybrid algorithm based on line-up competition algorithm and linear programming is presented. The proposed model and hybrid algorithm are applied to two benchmark examples in literature. The simulation results show that the proposed model and hybrid algorithm are effective for short-term scheduling of multipurpose batch plants. 相似文献
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Many continuous-time formulations have been proposed during the last decades for short-term scheduling of multipurpose batch plants. Although these models establish advantages over discrete-time representations, they are still inefficient in solving moderate-size problems, such as maximization of profit in long horizon, and minimization of makespan. Unlike existing literature, this paper presents a new precedence-based mixed integer linear programming (MILP) formulation for short-term scheduling of multipurpose batch plants. In the new model, multipurpose batch plants are described with a modified state-task network (STN) approach, and binary variables express the assignments and sequences of batch processing and storing. To eliminate the drawback of precedence-based formulations which commonly include large numbers of batches, an iterative procedure is developed to determine the appropriate number of batch that leads to global optimal solution. Moreover, four heuristic rules are proposed to selectively prefix some binary variables to 0 or 1, thereby reducing the overall number of binary variables significantly. To evaluate model performance, our model and the best models reported in the literature (S&K model and I&F model) are utilized to solve several benchmark examples. The result comparison shows that our model is more effective to find better solution for complex problems when using heuristic rules. Note that our approach not only can handle unlimited intermediate storage efficiently as well as the I&F model, but also can solve scheduling problems in limited intermediate storage more quickly than the S&K model. 相似文献
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Hyung Joon Kim Jae Hak Jung Minseok Kim In-Beum Lee 《Korean Journal of Chemical Engineering》1997,14(4):225-232
This paper describes a new scheduling solution for large number multi-product batch processes with complex intermediate storage
system. Recently many batch chemical industries have turned their attention to a more efficient system known as a pipeless
batch system. But existing plants need to change their systems to pipeless systems, piece by piece. In this case, current
systems are changed to pipeless systems by way of non critical process operations such as through the use of intermediate
storage. We have taken the conventional batch plant with a pipeless storage system as an objective process. Although the operation
of a pipeless storage system becomes more complex, its efficiency is very high. With this system, all of the storage should
be commonly used by any batch unit. For this reason, solving the optimal scheduling problem of this system with a mathematical
method is very difficult. Despite the attempts of many previous researches, there has been no contribution which solves the
scheduling of intermediate storage for complex batch processes. In this paper, we have developed a hybrid system of heuristics
and Simulated Annealing (SA) for large multi-product processes using a pipeless storage system. The results of this study
show that the performance and computational time of this method are superior to that of SA and Rapid Access Extensive Search
(RAES) methods. 相似文献