Comments (2)
This is a great idea. This would be closer to the idea of Adaptive Simulated Annealing:
https://en.wikipedia.org/wiki/Adaptive_simulated_annealing
When looking for the minimum of a continuous function, and while doing a move at each step, I would like to be able to adjust the size of the step based on temperature. As it gets closer to the end, the size of the step should decrease.
Generally speaking, I want access to temperature, somehow, from the move function. Also, ideally, access to the min and max values of temperature. This way, I could vary the size of the gaussian jump at each step, based on temperature.
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Hi! I know this is old but I'm doing this right now for my current project. You can easily make this change yourself -- just go into anneal.py and change T to self.T in the Annealer class, and then access in move() as self.T
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Related Issues (20)
- .auto() yields tmax == tmin, and negative remaining time HOT 2
- Problem in code HOT 1
- copy_state() returns None HOT 1
- Allow any type of state variable HOT 1
- multithreading HOT 2
- updates not printed out HOT 4
- Is it possible to perform a continuous problem with this package?
- Dependency injection for external data
- Travis builds failing HOT 1
- tsp example move() needs a fix
- question on multi-objective HOT 1
- Unit tests HOT 1
- ZeroDivisionError in anneal.py HOT 4
- Litterature reference for auto scheduling HOT 2
- Temperature and Energy stuck at zero HOT 1
- Litterature reference for simulated annealing HOT 2
- Annealing problem HOT 1
- Speeding Up the Calculation HOT 2
- Replacing lines to shorten output HOT 2
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