Reactive scheduling

An MILP framework for batch reactive scheduling with limited discrete resources. Comput. Chem. Eng., 28, 1059-1068. 

Reactive scheduling is an online procedure which modifies nominal schedules in reaction to the occurrence of an unexpected event. Reactive scheduling is traditionally used to handle short-term uncertainties in parameters as, e.g., processing times, or equipment failures. The underlying-models themselves usually do not incorporate information on the uncertainty. 

In the first part of this chapter (Section 9.2), we present an uncertainty conscious scheduling approach that combines reactive scheduling and stochastic scheduling by using a moving horizon scheme with an uncertainty conscious model. In this approach, it is assumed that decisions are made sequentially and that the effect of the revealed uncertainties can be partially compensated by later decisions. The sequence of decisions and observations is modeled by a sequence of two-stage stochastic programs. 

Neuhaus U, Gunther HO (2006) Development of a reactive scheduling system for application in the process industry, In Botta-Genoulaz V (ed) ILS2006, Proceedings of the First International Conference on Information Systems, Logistics and Supply Chain. Lyon... 

D. Ruiz, J. Canton, J.M. Nougues, A. Espufia, and L. Puigjaner. On-line fault diagnosis system support for reactive scheduling in multipurpose batch chemical plants. Computers and Chemical Engineering, 25 829-837, 2001. 

A Novel Proactive-Reactive Scheduling Approach In Chemical Multiproduct Batch Plants... 

Keywords reactive scheduling, proactive scheduling, multiproduct batch plants, uncertainty, MILP model... 

Nowadays, two approaches are mainly used to deal with uncertainty in process industry environments proactive and reactive scheduling. Proactive scheduling allows to fully exploit the flexibility of the process and, consequently to meet production goals to a... 

Proactive and reactive scheduling approaches are two different strategies aimed at dealing with unexpected events in the plant. In this work, an evaluation criterion is established in order to make feasible the aforementioned comparison. The proposed metric consists of a combination of the already stated objective function, OF, plus a rescheduling cost, weighted by the plant operational cost. Therefore, the evaluation criterion metric is given by Eq.(20). 

In order to combine the proactive and reactive scheduling approaches, a proactive-reactive control scheme is proposed in Fig. 2, based on the results obtained in the previous sections. The aforementioned scheme aims to encompass the advantages of both approaches. 

In this work, a comparison between proactive and reactive approaches has been carried out in terms of a new proposed evaluation criterion that considers earliness and tardiness, as well as rescheduling costs. This cost takes into account the total deviation from initial starting times and a batch reallocation cost which is proportional to the objective function. According to the presented case studies, the further from initially considered values uncertainty unveils, the better the reactive schedule performs according to the evaluation criterion. On the contrary, if uncertainty unveils as forecasted, and early in the time horizon, the best choice is the proactive approach. Future work will be focused on the validation and further improvement of the proactive-reactive control scheme. 

The sequencer and shop-floor control module of a scheduling system may track the work in progress as well as the status of the machines. It performs reactive scheduling functions based on this informtion. Such a module may be based on the axiom of locality, which impUes that if an unexpected event occurs, an effort is made to timit, as much as possible, the number of changes in the existing schedules when correcting the problem. 

Schedule and dispatch This partition is at the heart of MES operations, containing the primary entities involved in scheduling and dispatching. If the MES supports reactive scheduling, then the internal components must be able to share a common understanding of process description. Therefore, the model has a separate entity for process description, which is distinct from (and an instance of which is derived from a) process specification. We note with the tag active instances that unlike the entities in the other partitions, many Schedule and Dispatch entities can initiate actions. 

R D projects, see Research and development projects Reach, 1049 Reach distances, 1361 Reactive scheduling, 1733 Ready-made software, 68 Real estate brokers, 1476 Real-life scheduling, theoretical vs., 1732, 1733 Real output, 344... 

Eiben, A.E. and Smith, J.E., 2003. Introduction to Evolutionary Computing, Springer, Berlin. Elizabeth, S. and Roger, M.K., 1994. Knowledge-based reactive scheduling. Production Planning and Control, 5(2), 124-145. 

Real-time, online operation and control in closed loop including reactive scheduling. 

Fig. 18. Reactive scheduling scenario corresponding to online operation.

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