基于状态设备网络的改进间歇生产调度模型

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。     

基于状态设备网络的改进间歇生产调度模型

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。     

有并行设备的多目的间歇生产调度

针对有并行设备的多目的间歇生产调度问题,建立了以所有订单生产步骤排序和订单各阶段所选用分配规则为决策变量的调度优化模型,并提出了列队竞争算法求解该模型的有效个体表示方法及变异操作策略。实例计算表明:所提出方法的求解效率优于文献中所报道的方法,特别在求解有多台并行设备的调度问题时能得到比文献更好的结果,表现出其求解大规模复杂多目的调度问题的潜力。     

ZW多产品间歇过程调度及在线调整

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。     

基于TPN模型的间歇过程GA优化调度方法研究

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。     

多产品多级连续化工过程生产调度的研究

对多产品多级连续化工过程的生产调度问题进行了研究,考虑了设备清洗和设备生产效率下降对生产过程的影响.依据该过程具有组合和连续性特点,将该调度模型归结为一混合整数非线性规划问题(MINLP),以利润最大为目标,采用改进的遗传算法对该模型进行了求解.用一个三产品两级连续过程的例子说明了该算法的有效性.     

基于特定单元事件点的改进间歇生产调度模型

建立有效的间歇调度模型一直是生产调度问题调度研究的热点,而连续时间模型是优化短期间歇生产调度问题的有效工具。基于特定单元事件点的概念,建立一种改进的间歇调度连续时间混合整数线性规划(MILP)模型。该调度模型引入了新变量,使模型处理物料在不同设备间的传输过程更加灵活。结果表明,提出的改进模型只需要较少的事件点,就可以快速有效处理无限中间存储(UIS)间歇调度问题。     

新的多产品间歇生产调度的MILP模型

提出了一种新的多产品厂间歇调度问题的连续时间混合整数线性规划 (MILP)模型,该模型的整数变量体系不依赖于时间块(或者事件点)的概念,并且利用了变量物理概念上的对称互补性,使得与传统的建模方法相比不仅整数变量的数目减少了一半以上,而且建模思想、建模理论都有了新的改进.通过对一个算例的考察证实了新模型可以快速地求得全局最优解.     

列队竞争算法求解多产品间歇生产过程排序问题

由于组合爆炸特性,多产品厂的排序问题很难求解大规模甚至中等规模的问题.采用一种新的随机型优化搜索算法--列队竞争算法来对该问题进行求解,引入新的选择策略和变异方法.计算表明同已有的方法相比,该方法求解效率高、收敛速度快、使用简单方便,是一种求解多产品间歇过程排序问题的有效算法,为多目的厂间歇过程排序研究提供了新思路.     

炼油企业全厂调度优化系统的设计与开发

生产调度优化对于炼油企业提高经济效益、增强市场响应速度有着重要的作用。本文设计并开发出一款图形化炼厂生产调度优化软件,采用MVC架构技术,实现了调度优化建模的图形化,可以方便组态炼油厂调度模型;将开源优化代码Coin-OR移植为调度优化软件的求解器,实现了求解器与图形化建模接口的连接;丰富的报表输出,让现场操作工可以各种形式获得调度优化结果;完善的内部模型数据管理和丰富的外部数据接口,包括原油性质指标库和原油评价数据库接口、成品油性质指标库等。仿真结果表明,该软件能够优化出符合炼厂生产实际的调度优化排产方案。     

A novel precedence-based and heuristic approach for short-term scheduling of multipurpose batch plants

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.     

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

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.     

A simpler better slot-based continuous-time formulation for short-term scheduling in multipurpose batch plants

Short-term scheduling of multipurpose batch plants is a challenging problem for which several formulations exist in the literature. In this paper, we present a new, simpler, more efficient, and potentially tighter, mixed integer linear programming (MILP) formulation using a continuous-time representation with synchronous slots and a novel idea of several balances (time, mass, resource, etc.). The model uses no big-M constraints, and is equally effective for both maximizing profit and minimizing makespan. Using extensive, rigorous numerical evaluations on a variety of test problems, we show that in contrast to the best model in the literature, our model does not decouple tasks and units, but still has fewer binary variables, constraints, and nonzeros, and is faster.     

Design,synthesis and scheduling of multipurpose batch plants via an effective continuous-time formulation

Design, synthesis and scheduling issues are considered simultaneously for multipurpose batch plants. An earlier proposed continuous-time formulation for scheduling is extended to incorporate design and synthesis. Processing recipes are represented by the State-Task Network (STN). The superstructure of all possible plant designs is constructed according to the potential availability of all processing/storage units. The proposed model takes into account the trade-offs between capital costs, revenues and operational flexibility. Computational studies are presented to illustrate the effectiveness of the proposed formulation. Both linear and nonlinear models are included, resulting in MILP and mixed-integer nonlinear programming (MINLP) problems, respectively. The MILP problems are solved using a branch and bound method. Globally optimal solutions are obtained for the nonconvex MINLP problems based on a key property that arises due to the special structure of the resulting models. Comparisons with earlier approaches are also presented.     

批处理过程优化调度研究综述--1.MILP调度方法的描述框架

综述化工批处理过程调度建模研究及其实际应用。计划／调度在企业生产管理中起着承上启下的作用，合理的计划调度不但能提高企业的服务水平、降低存储费用，而且还能提高企业的生产能力、加深对过程机制及关键数据的理解。整数规划方法应用于批处理过程计划调度，具有较好的适用性和扩展性，解的性质良好，在批处理过程调度研究得到广泛的应用。     

An MILP continuous-time approach to short-term scheduling of resource-constrained multistage flowshop batch facilities

This work presents a new MILP mathematical formulation for the resource-constrained short-term scheduling of flowshop batch facilities with a known topology and limited supplies of discrete resources. The processing structure is composed of multiple stages arranged in series and several units working in parallel at each one. All production orders consist of a single batch and follow the same processing sequence throughout the plant. The proposed MILP approach is based on a continuous time domain representation that relies on the notion of order predecessor and accounts for sequence-dependent setup times. Assignment and sequencing decisions are independently handled through separate sets of binary variables. A proper formulation of the sequencing constraints provides a substantial saving in sequencing variables and constraints. By postulating a pair of conditions for the simultaneous execution of processing tasks, rather simple resource constraints requiring a few extra binary variables are derived. The proposed MILP scheduling approach shows a remarkable computational efficiency when applied to real-world problems.     

Simultaneous regular and non-regular production scheduling of multipurpose batch plants: A real chemical–pharmaceutical case study

Regular and non-regular production can often be found in multipurpose batch plants, requiring two distinct operating strategies: campaign and short-term production. This paper proposes a solution approach for simultaneous scheduling of campaign and short-term products in multipurpose batch plants. Regular products follow a cyclic schedule and must cover several product deliveries during the scheduling horizon, while non-regular products have a non-cyclic schedule. The proposed approach explores the Resource-Task Network (RTN) discrete-time formulation. Moreover, a rolling horizon approach, and reformulation and branching strategies have been applied to deal with the computational complexity of the scheduling problem. Real case instances of a chemical–pharmaceutical industry are solved, showing the applicability of the solution approach.     

批处理过程优化调度研究综述——2.MILP调度

详细阐述MILP建模的关键技术和现有的有关参考文献,同时给出MILP调度实施框架和已经报道的成功应用。在此基础上,指出进一步的研究方向。