Correct predictions are in blue. If we detect only a subset of a labelled sentence, we highlight the caught part as blue, the missing part light blue. False positives are in green and false negatives are in red.

Problem Multi-Machine_Assignment_Scheduling — Constraint detection

In this model there are n tasks and m dissimilar machines . Each task can be processed on any and only one machine . Each machine can handle only one task at a time . The processing cost and the processing time of task i on machine j are $ c _ -LCB- ij -RCB- $ and $ p _ -LCB- ij -RCB- $ , respectively . Processing of task $ i $ can only begin after the release date $ r_i $ , and must be completed at the latest by the due date $ d_i $ . The problem is to carry out all the tasks at the least possible cost .

Problem Multi-Machine_Assignment_Scheduling — Detection of the decisions and objects to be modeled

In this model there are n tasks and m dissimilar machines . Each task can be processed on any and only one machine . Each machine can handle only one task at a time . The processing cost and the processing time of task i on machine j are $ c _ -LCB- ij -RCB- $ and $ p _ -LCB- ij -RCB- $ , respectively . Processing of task $ i $ can only begin after the release date $ r_i $ , and must be completed at the latest by the due date $ d_i $ . The problem is to carry out all the tasks at the least possible cost .

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