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Problem data.
Problem type.
If set, it defines a strict date, and each task must finish before this.
Additional info stored in the source file. The horizon is a date where we are sure that all tasks can fit before it.
The release date is defined in the rcpsp base format, but is not used.
The tardiness cost is defined in the rcpsp base format, but is not used.
The mpm_time is defined in the rcpsp base format, but is not used. It is defined as the minimum makespan in case of interruptible tasks.
Data used by the problem generator.
The due date is defined in the rcpsp base format, but is not used.
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The duration of the task when this recipe is selected.
In the general case, demand must be >= 0. In the consumer/producer case, it can be < 0. Note that in this case, the tasks always have a duration of zero. Thus the effect of the demand (increase or decrease of the current usage) happens at the start of the task.
This parallel list indicates which resource index (in the main problem) the above demand corresponds to.
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The max capacity of the cumulative.
This field is used only in the consumer/producer case. It states the minimum capacity that must be valid at each time point.
Indicates if the resource is renewable, that is if a task demands d from this resource, then the available capacity decreases by d at the start of the task and increases by d at the end of the task.
If non zero, then each unit of capacity will incur a cost of unit_cost.
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The indices of the successors tasks in the main problem.
The list of possible ways to execute the task.
If the current task has n successors and m recipes then this is an n x m matrix where each entry at line i is a vector with the same length as the number of recipes for the task successor[i]. If recipe m1 is chosen for the current task, and recipe m2 is chosen for its successor i, we have: start(current_task) + delay[i][m1][m2] <= start(successor_task).