This repository looks similar to https://www.omnicalculator.com/other/dating-theory but with more flexibility and FOSSness. However it is known that this suffers from a few problem:
- Given X people and you want the Top Y (instead of Top 1) results, what is the optimal sampling point?
- Given X amount of time, when should one start to settle for the next option as hopefully the top Y% of the available option?
Ref:
Original Source: https://bellemanwesley.medium.com/dont-follow-the-37-rule-511b19b14f21
TED's extension on Top-N problem: https://ideas.ted.com/when-should-you-settle-down/
Independent extension on Top-N problem: https://blogs.gartner.com/jitendra-subramanyam/long-look-leap/
Time-anchored Secretary Problem: http://bearlamp.com.au/the-application-of-the-secretary-problem-to-real-life-dating/
More Visualization https://www.imrankhan.dev/pages/Solving%20the%20secretary%20problem%20with%20Python.html
This repository looks similar to https://www.omnicalculator.com/other/dating-theory but with more flexibility and FOSSness. However it is known that this suffers from a few problem:
Ref:
Original Source: https://bellemanwesley.medium.com/dont-follow-the-37-rule-511b19b14f21
TED's extension on Top-N problem: https://ideas.ted.com/when-should-you-settle-down/
Independent extension on Top-N problem: https://blogs.gartner.com/jitendra-subramanyam/long-look-leap/
Time-anchored Secretary Problem: http://bearlamp.com.au/the-application-of-the-secretary-problem-to-real-life-dating/
More Visualization https://www.imrankhan.dev/pages/Solving%20the%20secretary%20problem%20with%20Python.html