Comments (3)
robfairh
commented on July 29, 2024
1
It checks first if there are preferences greater than 0. If there are, it checks if they are equal. If they are different, then it deploys the one with the highest preference. If they are equal, it checks if they have a sharing preference. If it does, then it deploys based on that. If it doesn't it deploys the min number of facilities.
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gwenchee
commented on July 29, 2024
@robfairh Could you describe how this sharing capability works here?
With respect to constraint, preferences etc. Like what happens first?
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robfairh
commented on July 29, 2024
closed by #279
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Related Issues (20)
- combine demand driven inst and supply driven inst HOT 3
- D3ploy doesn't record the capacity of the mixer when it has multiple inputs for a commodity HOT 10
- pytest - ImportError: cannot import name 'main' HOT 21
- Buffer Type change HOT 1
- D3ploy is not running FFT properly on numpy 1.16.4 HOT 10
- Add function in tester.py to obtain cumulative difference between demand and supply HOT 1
- Mixer doesn't record the demand of all the input commodities. HOT 1
- constraint commodity capability bug HOT 1
- d3ploy fails to record the capacity of mixers deployed with multiple inputs HOT 2
- D3ploy fails to record the capacity of mixers when they are deployed using the same commodity. HOT 1
- Buffer malfunctioning HOT 6
- D3ploy Doesn't Work HOT 13
- update config.yml file to include all the new tests HOT 3
- calc_demand takes the values of the demand_eq HOT 2
- Some of the methods don't actually use the back_steps HOT 1
- Some of the prediction methods don't have the capability to look forward. HOT 3
- Installed cap should't be used with the back end HOT 3
- Installation Issue HOT 16
- Update Documentation HOT 2
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