Traveling Salesman Problem-Based Integration of Planning, Scheduling, and Optimal Control for Continuous Processes
Traveling Salesman Problem-Based Integration of Planning, Scheduling, and Optimal Control for Continuous Processes
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DOI：
10.1021/acs.iecr.7b01122
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发表时间：
2017-09
影响因子：
4.2
通讯作者：
Vassilis M. Charitopoulos;V. Dua;L. Papageorgiou
中科院分区：
文献类型：
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作者：
Vassilis M. Charitopoulos;V. Dua;L. Papageorgiou
流程工业的高级决策需要有效利用不同决策级别的信息。传统上，计划、调度和最优控制问题是以一种解耦的方式解决的，忽略了它们之间的强相互依赖性。综合计划、调度和最优控制(IPSC)旨在解决这一问题。IPSC的形成，导致了一个大规模的非凸混合整数非线性规划问题。在目前的工作中，我们提出了一种新的方法来解决连续过程的IPSC问题，旨在降低模型和计算复杂度。对于计划和调度，采用基于旅行商问题的公式，其中计划周期以离散时间建模，而每周内的调度以连续时间建模。建议的IPSC框架的另一个特点是引入了积压、空闲的生产时间和多个客户。所得到的问题是一个混合整数规划问题，并且有不同的求解策略。
Advanced decision making in the process industries requires efficient use of information available at different decision levels. Traditionally, planning, scheduling, and optimal control problems are solved in a decoupled way, neglecting their strong interdependence. Integrated planning, scheduling and optimal control (iPSC) aims to address this issue. Formulating the iPSC, results in a large scale nonconvex mixed integer nonlinear programming problem. In the present work, we propose a new approach for the iPSC of continuous processes aiming to reduce model and computational complexity. For the planning and scheduling, a Traveling Salesman Problem-based formulation is employed, where the planning periods are modeled in discrete time while the scheduling within each week is in continuous time. Another feature of the proposed iPSC framework is that backlog, idle production time, and multiple customers are introduced. The resulting problem is a mixed integer programming problem and different solution strategi...