Sequencing/scheduling module

The constraints considered in the mathematical formulation are divided into two modules. The first deals with the mass balance constraints and the second with the sequencing and scheduling constraints. The mass balance constraints for the case where there is no central storage are slightly different to those for the case where there is. The mass balances for each are described in the mass balance module below. The sequencing and scheduling module will be described, for both cases, in a subsequent section. The nomenclature for all the sets, variables and parameters can be found in the nomenclature list. 

On the upper level, the scheduling module allocates the equipment which is required for processing the next batch. In these decisions, the current equipment allocation, the equipment properties and a cost-function are taken into account. The allocation is performed in a sequence according to increasing starting times of the batches. 

A new optimisation structure (Fig.2) for the scheduling of operational activities in a real-world pipeline network (Fig.l) has been addressed in this paper. In addition, a new computational procedure was developed, the Pre-Analysis module. The real scenario could be addressed mostly due to Pre-Analysis scalability. The considered scenario is particularly complex and involves more nodes and pipes, compared to the one discussed in a previous work [5]. In order to address this scenario, a decomposition approach was used. This decomposition relied on a Resoince Allocation block, which takes into accoimt production/consumption functions and typical lot sizes to determine a set of candidate sequences of pumping. Furthermore, a Pre-Analysis block uses candidate sequences to determine temporal and volume parameters. These parameters were used in a continuous-time MILP model, which indeed determines the short-term scheduling of each batch in each node of the pipeline network. The implemented structure can be used, for instance, to identify system bottlenecks and to test new operational conditions. Computation time has remained at few CPU seconds. The proposed approach have allowed that a monthly planning of production and consumption be detailed in short-time scheduling operations within the considered pipeline network. Thus, operational insights can be derived from the obtained solutions. As an ongoing research, the Pre-Analysis would be used to determine other parameters for the MILP model. 

The five priority rules mentioned in the previous section, WSPT, HDD, LPT, SST, and CP, are fairly important. They provide optimal sequences in some very simple cases and serve as heuristics for more complicated scheduling models. It is useful to know the properties of these priority rules when designing a complicated computer-based scheduling system. Different modules in such a system may use at given times one of these rules to sequence a subset of the jobs. Or a composite priority rule may be constructed by combining two or more of these simple priority rules in order to minimize a mixture of various objectives. A more in-depth discussion of these five simple priority rules follows. 

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. 

The distinction between continuous and batch opo-ations is not as great as is sometimes thought. All steady-state processes include a variety of batch operations such as filling tanks from tmcks and catching samples according to a predetermined schedule. Moreover, the sequence of instmctions within a procedure or module is essentially the same as the sequence of instmctions in a batch process. 

Control Step Scheduling and Data Path Allocation. Control step scheduling (CSTEP) and data path allocation (EMUCS) are the last of the major phases of the Workbench shown in Figure 9-1. The control step sequencing and data path allocation tools synthesize modules to perform the operations and transfer and store the values it finds in the VT. They assign all the operators in the VT to control steps and bind individual values and operators in the VT to specific modules in the synthesized structure. Only the EMUCS data path allocation tool has been integrated into the CORAL system. 

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