Route. Schedule. Plan. Assign. Pack. Solve
Organizations whose employees work multiple shifts need to schedule sufficient workers for each daily shift. Typically, the schedules will have constraints, such as "no employee should work two shifts in a row". Finding a schedule that satisfies all constraints can be computationally difficult.
The following sections present two examples of employee scheduling problems, and show how to solve them using the CP-SAT solver.
Using and Understanding ortools' CP-SAT: A Primer and Cheat Sheet
CP-SAT over CBC for MIP, is it worthwhile?
The CP solver was developed 10 years ago. 3-4 years ago, we started the SAT/CP solver. Its performances are way better than the CP one.
How to speed up sat cp using strategies
Set the amount of possible unique values for variables in ORTOOLS CP-SAT
[or-tools/examples/python/shift_scheduling_sat.py](https://github.com/google/or-tools/blob/stable/examples/python/shift_scheduling_sat.py()
def AddLinearExpressionInDomain(self, linear_expr, domain):
OR-Tools CP-SAT solver: count successive NewBoolVar occurrences
If you want to constrain the length of a sequence, you should look at the shift_scheduling example
In particular, the soft sequence constraint. The idea is the following, for every starting point, you want to forbid 010, 0110, 01110, ..., 0111110 and 01111111111110 (0110 means work[start] is false, work[start + 1] is true, work[start + 2] is true, work[start + 3] is false.
To increase computational speed, the CP-SAT solver works over the integers. This means you must define your optimization problem using integers only.
let's start with a simple example problem in which there are:
Three variables, x, y, and z, each of which can take on the values: 0, 1, or 2. One constraint: x ≠ y
Fairness is the most complex question in OR. You need to try to capture what you want with equations as sample as possible.
Std deviation, variance are not simple. Minimizing max(worked per person) - min(worked per person);is simple.