TimefoldAI / TimefoldAI/timefold-solver

Feat: Make time gradient calculation more flexible

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#1,138 3 comments 0 reactions 0 assignees View on GitHub

A pull request for this has already been merged.

  • #1157 by @triceo — merged
process/needs triage
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Java
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Description

Is your feature request related to a problem? Please describe.
Finding the right termination config for time gradient based algorithms like simulated annealing is pretty hard especially for benchmarks. If I configure a maximum solving time of 10 minutes and a unimproved seconds spent limit of 30 seconds the 30 seconds spent limit is influencing the progress of the time gradient. The same is true if I configure a best score limit. It is not possible to configure an unimproved seconds and best score spent limit without influencing the time gradient.

This is especially problematic for benchmarking. I want to determine how long my algorithm takes until it reaches a specific score and I want it to behave like the production environment. But if I define a best score limit this influences the time gradient and therefore the algorithm behaves different than without the limit.

Describe the solution you'd like
I like to be able to configure a time based spent limit together with unimproved seconds or best score limit without effecting the time gradient. E.G. if I configure 10 minutes spent limit with 30 seconds unimproved spent limit, the time gradient should only depend on the progress of the 10 minutes. Maybe you could add a boolean flag to the termination configs to let the user decide if a termination criterion should be considered by the time gradient calculation.

Describe alternatives you've considered
I don't know any working alternative.

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First steps

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  3. Fork the repository and make your change on a branch.
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Research direction

Begin by locating the time gradient calculation and the termination configuration handling described in the issue. Compare how maximum solving time, unimproved seconds, and best score limits affect the gradient; done means these criteria can be configured without affecting a time-based gradient when requested, with coverage for the benchmarking scenario.

Written by the indexing model from the issue text.

Assessment

Tech stack
java
Domain
ai
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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