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integration of scheduling and control under uncertainties: Review and challenges

CHEMICAL ENGINEERING RESEARCH & DESIGN 2016年 116卷 98-113页

作者： Dias, Lisia S. Ierapetritou, Marianthi G. Rutgers State Univ Dept Chem & Biochem Engn 98 Brett Rd Piscataway NJ 08854 USA

In order to achieve optimal operational conditions, the integration of decision-making across different layers of a company and the consideration of uncertain parameters in view of dynamic market conditions are essential. In this article, we review some of the efforts done by the process system engineering and process control communities aiming to optimize performance in a process industry;specifically in the areas of control, scheduling and their integration under process uncertainties. First, uncertainties in process scheduling and control are analyzed, and the different mathematical approaches to describe and optimize problems under uncertainty are described. Recent advances and relevant frameworks for scheduling and control under uncertainties are presented, and efforts for the integration of scheduling and control are reviewed. (C) 2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Process control Production scheduling Process uncertainties integration of scheduling and control

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integration of scheduling and control for batch process based on generalized Benders decomposition approach with genetic algorithm

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COMPUTERS & CHEMICAL ENGINEERING 2021年 145卷 107166-107166页

作者： Ji, Nan Gu, Xingsheng East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China

Batch process plays an important role in various fields of industrial production, such as chemical engineering and pharmacy, given its characteristics such as small batch size, flexible production, and additional value of the product. Efforts to integrate the scheduling and process control for improving the benefits of batch process are recent. The integration of scheduling and process control is described by state equipment network which is closely related to the processing variables due to the feature of the network structure of the batch process where material splitting and mixing are allowed. The integrated formulation invokes logical disjunctions and operational dynamics which represents a typical mixed-logic dynamic optimization (MLDO) problem. To solve such a MLDO problem, we transform it into a mixed-integer nonlinear program (MINLP) using the Big M reformulation and the simultaneous collocation method. Then, the MINLP problems are solved through a generalized Benders decomposition (GBD) approach and genetic algorithm. The decomposed master problem is a scheduling problem with variable processing times, processing costs, and the Benders cut. Accordingly, the genetic algorithm is implemented to increase benefit. The primal problem comprises a set of separable dynamic optimization problems in the processing units. By collaboratively optimizing the process scheduling and dynamics, the proposed method substantially improves the overall economic performance of the batch production. At last, the feasibility and superiority of the proposed integration model and optimization algorithm can be determined by dealing with specific production instances. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Batch process integration of scheduling and control Production scheduling Process control Global optimization Generalized Benders decomposition

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integration of scheduling and control for Batch Processes Using Multi-Parametric Model Predictive control

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AICHE JOURNAL 2014年第9期60卷 3169-3183页

作者： Zhuge, Jinjun Ierapetritou, Marianthi G. Rutgers State Univ Dept Chem & Biochem Engn Piscataway NJ 08854 USA

integration of scheduling and control results in Mixed Integer Nonlinear Programming (MINLP) which is computationally expensive. The online implementation of integrated scheduling and control requires repetitively solving the resulting MINLP at each time interval. (Zhuge and Ierapetritou, Ind Eng Chem Res. 2012;51: 8550-8565) To address the online computation burden, we incorporare multi-parametric Model Predictive control (mp-MPC) in the integration of scheduling and control. The proposed methodology involves the development of an integrated model using continuous-time event-point formulation for the scheduling level and the derived constraints from explicit MPC for the control level. Results of case studies of batch processes prove that the proposed approach guarantees efficient computation and thus facilitates the online implementation. (C) 2014 American Institute of Chemical Engineers

关键词： integration of scheduling and control event-point scheduling formulation multi-parametric Model Predictive control mixed integer nonlinear programming batch processes

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integration of scheduling and control for the no-wait batch process: A decomposition method

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CHEMICAL ENGINEERING SCIENCE 2022年 260卷

作者： Ji, Nan Gu, Xingsheng East China Univ Sci & Technol Key Lab Smart Mfg Energy Chem Proc Minist Educ Shanghai 200237 Peoples R China

The batch process plays an important role in various fields of industrial production. Among them, the production processes that have specific requirements for operational continuity in each processing stage such as metallurgical, steelmaking, and pharmaceutical, should consider the no-wait constraints to meet the production reality. The batch process with no-wait constraints is a typical NP-hard problem. A new decomposition method with an improved genetic algorithm was proposed to solve the integration problem for the no-wait batch process. The integrated formulation represents a typical mixed-logic dynamic optimization (MLDO) problem which invokes logical disjunctions and operational dynamics. To solve such an MLDO problem, we transform it into a mixed-integer nonlinear program (MINLP) using the Big M reformulation and the simultaneous collocation method. Considering the structure and characteristics of the no-wait problem, an improved algorithm based on the previous GA-GBD algorithm is proposed. By collaboratively optimizing the process scheduling and dynamics, the proposed method substantially improves the overall economic performance of the batch production. At last, specific production instances are tested to demonstrate the feasibility and superiority of the proposed integration model of the no-wait batch process and optimization algorithm. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Batch process integration of scheduling and control No-wait scheduling Process control Global optimization Generalized Benders decomposition

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Simultaneous mixed-integer dynamic scheduling of processes and their energy systems

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AICHE JOURNAL 2022年第8期68卷 e17741-e17741页

作者： Baader, Florian Joseph Bardow, Andre Dahmen, Manuel Forschungszentrum Julich Inst Energy & Climate Res Energy Syst Engn IEK 10 D-52425 Julich Germany Rhein Westfal TH Aachen Fac Mech Engn Aachen Germany Swiss Fed Inst Technol Energy & Proc Syst Engn Zurich Switzerland Rhein Westfal TH Aachen Inst Tech Thermodynam Aachen Germany

Increasingly volatile electricity prices make simultaneous scheduling optimization desirable for production processes and their energy systems. Simultaneous scheduling needs to account for both process dynamics and binary on/off-decisions in the energy system leading to challenging mixed-integer dynamic optimization problems. We propose an efficient scheduling formulation consisting of three parts: a linear scale-bridging model for the closed-loop process output dynamics, a data-driven model for the process energy demand, and a mixed-integer linear model for the energy system. Process dynamics is discretized by collocation yielding a mixed-integer linear programming (MILP) formulation. We apply the scheduling method to three case studies: a multiproduct reactor, a single-product reactor, and a single-product distillation column, demonstrating the applicability to multiple input multiple output processes. For the first two case studies, we can compare our approach to nonlinear optimization and capture 82% and 95% of the improvement. The MILP formulation achieves optimization runtimes sufficiently fast for real-time scheduling.

关键词： demand response integration of scheduling and control mixed-integer dynamic optimization mixed-integer linear programming simultaneous scheduling

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An integrated framework for scheduling and control using fast model predictive control

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AICHE JOURNAL 2015年第10期61卷 3304-3319页

作者： Zhuge, Jinjun Ierapetritou, Marianthi G. Rutgers State Univ Dept Chem & Biochem Engn Piscataway NJ 08854 USA

integration of scheduling and control involves extensive information exchange and simultaneous decision making in industrial practice (Engell and Harjunkoski, Comput Chem Eng. 2012;47:121-133;Baldea and Harjunkoski I, Comput Chem Eng. 2014;71:377-390). Modeling the integration of scheduling and dynamic optimization (DO) at control level using mathematical programming results in a Mixed Integer Dynamic Optimization which is computationally expensive (Flores-Tlacuahuac and Grossmann, Ind Eng Chem Res. 2006;45(20):6698-6712). In this study, we propose a framework for the integration of scheduling and control to reduce the model complexity and computation time. We identify a piece-wise affine model from the first principle model and integrate it with the scheduling level leading to a new integration. At the control level, we use fast Model Predictive control (fast MPC) to track a dynamic reference. Fast MPC also overcomes the increasing dimensionality of multiparametric MPC in our previous study (Zhuge and Ierapetritou, AIChE J. 2014;60(9):3169-3183). Results of CSTR case studies prove that the proposed approach reduces the computing time by at least two orders of magnitude compared to the integrated solution using mp-MPC. (c) 2015 American Institute of Chemical Engineers AIChE J, 61: 3304-3319, 2015

关键词： integration of scheduling and control piece-wise affine approximation fast model predictive control Multiparametric model predictive control mixed integer nonlinear programming

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Closed-loop scheduling in a canned food factory 21st

Closed-loop Scheduling in a canned food factory

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Palacin, C. G. Vilas, C. Alonso, A. A. Pitarch, Jose L. de Prada, C. Univ Valladolid Syst Engn & Automat Control Dept Valladolid Spain Inst Invest Marinas Punta Betin Bio Proc Engn Grp CSIC Vigo Spain

This paper addresses the problem of closed-loop operation of scheduling, together with the interaction of control and scheduling, for a class of processes that appear very often in industry: those that combine continuous production lines with parallel batch units that share some resources. The paper presents a novel approach to this problem, including batching and a new type of precedence in the assignment problem. It also considers the effect of shared resources on the duration of the cycle time of the batch units. The approach is illustrated with a real-life example of a canned tuna factory Copyright (C) 2020 The Authors.

关键词： integration of scheduling and control shared resources tuna cans sterilisation process optimisation continuous-batch process scheduling

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