Integration of scheduling and control under uncertainties: Review and challenges

Dias, Luís M. S.; Ierapetritou, Marianthi G.

doi:10.1016/j.cherd.2016.10.047

Cited by 74 publications

(41 citation statements)

References 80 publications

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“…While the formulations and models described in the last subsection can derive optimal schedules for a provided system, weather dynamics require dynamic approaches to cope with the associated uncertainties. Several authors provide a review of current methods for the dynamic scheduling in production environments, e.g., [32][33][34]. Therefore, they provide a more or less common classification of these approaches, which is summarized below:…”

Section: Dynamic Scheduling Approachesmentioning

confidence: 99%

Evaluation of Loading Bay Restrictions for the Installation of Offshore Wind Farms Using a Combination of Mixed-Integer Linear Programming and Model Predictive Control

et al. 2019

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Featured Application: This article demonstrates a combination of Mixed-Integer LinearProgramming with methods usually applied for short-term control, namely the Model Predictive Control scheme, to achieve decision support for the scheduling of installation activities for offshore wind farms. The general approach applies to several areas of application, where time-dependent uncertainties complicate mid-to long-term planning.Abstract: The installation of offshore wind farms poses particular challenges due to expensive resources and quickly changing weather conditions. Model-based decision-support systems are required to achieve an efficient installation. In the literature, there exist several models for scheduling offshore operations, which focus on vessels but neglect the influence of resource restrictions at the base port and uncertainties involved with weather predictions. This article proposes a Mixed-Integer Linear Programming model for the scheduling of installation activities, which handles several installation vessels as well as restrictions about available cargo bridges at the port. Additionally, the article explains how this model can be combined with a Model Predictive Control scheme to provide decision support for the scheduling of offshore installation operations. The article presents numerical studies of the effects induced by resource restrictions and of different parametrizations for this approach. Results show that even small planning windows, paired with comparably low computational times, achieve reasonably good results. Moreover, the results show that an increase in vessels comes at diminishing returns concerning the installation efficiency. Therefore, the results indicate that available good-weather windows primarily limit efficiency.

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Section: Dynamic Scheduling Approachesmentioning

confidence: 99%

Evaluation of Loading Bay Restrictions for the Installation of Offshore Wind Farms Using a Combination of Mixed-Integer Linear Programming and Model Predictive Control

et al. 2019

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“…The computational requirements of the problem prevent online implementation. Dias and Ierapetritou demonstrate the benefits of using robust model predictive control in ISC to optimally address process uncertainty in continuous chemical processes [32].…”

Section: Reactive Integrated Scheduling and Controlmentioning

confidence: 99%

“…Many previous works considering reactive ISC are outlined in Table 2. For a complete review of ISC under uncertainty, the reader is directed to a recent review by Dias and Ierapetritou [32]. Zhuge and Ierapetritou demonstrate increased profit from closed-loop implementation (over open-loop implementation) of combined scheduling and control in the presence of process disturbances [47].…”

Section: Reactive Integrated Scheduling and Controlmentioning

confidence: 99%

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

et al. 2017

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Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of process dynamics, and closed-loop integrated scheduling and control responsive to process disturbances and market fluctuations. Progressive economic benefit from dynamic rescheduling and integrating scheduling and control is shown on a continuously stirred tank reactor (CSTR) benchmark application in closed-loop simulations over 24 h. A fixed horizon integrated scheduling and control formulation for multi-product, continuous chemical processes is utilized, in which nonlinear model predictive control (NMPC) and continuous-time scheduling are combined.

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“…Extensive prior research has been conducted on integrated scheduling and control, including several literature review articles [1][2][3][4]31,32]. Mahadevan et al incorporate control level considerations such as grade transition costs in production scheduling [33].…”

Section: Literature Reviewmentioning

confidence: 99%

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

et al. 2017

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Abstract:A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC) and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP) dynamic optimization problems and mixed-integer linear programming (MILP) problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation's closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR) application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure.

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Integration of scheduling and control under uncertainties: Review and challenges

Cited by 74 publications

References 80 publications

Evaluation of Loading Bay Restrictions for the Installation of Offshore Wind Farms Using a Combination of Mixed-Integer Linear Programming and Model Predictive Control

Evaluation of Loading Bay Restrictions for the Installation of Offshore Wind Farms Using a Combination of Mixed-Integer Linear Programming and Model Predictive Control

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

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