This test shows how the linear programming solver is used to solve a capacity allocation problem in an optimal way.
The problem input consists of:
- A set of time buckets.
- A set of demands, each with a due bucket, a quantity and a priority.
- A set of resources, each with an available capacity per time bucket.
- A set of loads, i.e. demands requiring some time on one or more resources.
The problem is subject to the following constraints:
- For each time bucket and each resource:
sum of capacity used by each demand <= capacity available in the resource bucket - For each demand:
sum of planned quantities in different buckets <= requested demand quantity
The LP problem solves for a hierarchy of goals.
- Minimize the shortness of demand of priorities 1, 2 and 3
- Minimize the lateness of demand of priorities 1, 2 and 3
- Minimize the early use of capacity (ie use capacity before the due date)