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Evolution. Schedules are competing for being there. Every second 10000 or so are born and are mostly killed by the control program which let live only the top schedules according to the 30+ criteria set in the script.
Random (but perhaps clever) mutation and non-random selection, that's under the hood.
At first, the top schedule is a random one and not feasible at all. After a million (or a billion, that depends) generations the first feasible one appears and from there on, evolution produces more and more perfect schedules.
For every processor core, at least one evolution is going on. Each at least slightly different one. The program can spread across many computers and there may be as many as 100 or more parallel evolutions going on. They talk occasionally (via internet) and exchange their champions.
It has been 10 years long real life experiment, which went very well. A lot of schools involved, teachers and students and some academic papers published. Now it's time to spread it.
so, parallel genetic algorithm based scheduling app with (ranked?) constraints?
In what way is it more automatic than existing similar apps?
presumably you still need to give it a list of constraints (say a few thousand constraints), possibly in a spreadsheet, some soft, some hard and it spits out a few of the top solutions or presumably an error if the hard constraints cannot be met?
What can it do that, say, optaplanner can't do?