Add acceptance criteria to both #99
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I was resetting the best energy incorrectly. That should only be reset if the candidate is better.
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When using the heuristic to optimise the objective function it was doing so in ignorance of the constraints. This add the ability to pass a `acceptance_criteria` to both heuristics which gives a bound on some measure. In practice it's used in `schedule.heuristic` when an objective function is passed. In this case it passes the violation counts as an `acceptance_criteria` to ensure that as each heuristic goes through the search space optimising the objective function it will only accept a solution if this does not add any constraint violations. TLDR: The modified tests show a good example of this. The objective function optimisation was giving a schedule that was in fact invalid. This has now been fixed.
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For clarity, this is a fork of #98, once that's merged this diff should be clearer.
When using the heuristic to optimise the objective function it was doing
so in ignorance of the constraints.
This add the ability to pass a
acceptance_criteriato both heuristicswhich gives a bound on some measure. In practice it's used in
schedule.heuristicwhen an objective function is passed. In this caseit passes the violation counts as an
acceptance_criteriato ensurethat as each heuristic goes through the search space optimising the
objective function it will only accept a solution if this does not add
any constraint violations.
The modified tests show a good example of this. The objective function
optimisation was giving a schedule that was in fact invalid. This has
now been fixed.