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The process involves: an optimal stations location modeling and a discrete simulation process for determining the ideal number of bicycles and the number of parking lots per station.
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The model is applied to derive an optimal station roll-out scheme for Southern California.
In the next step, the stations with maximum VOI is selected as optimal stations.
A detailed theoretical analysis is provided to derive the optimal station attempt probability which leads to a proportional fair allocation of station throughputs.
Pelz' study employed a spatial and statistical methodology to determine optimal station locations.
A simple and effective mathematical method to calculate optimal station-keeping manoeuvres by means of electric propulsion is suggested.
Third, we investigate the optimal train fare design that leads to the system optimal station choice.
Finally, the optimal station locations are ranked by using combined utility scores gained from the first and second steps.
Second, we examine the system optimal station choice that assumes all of the commuters cooperate and minimizes their total travel cost.
If the density changes linked to such an activity are spatially known, one is then able to predict if the surface gravity effects are detectable and even to set up the optimal station positioning.
Therefore, it is obvious that the PEV fast charging demand is unpostponable and uninterruptible, but the PEVs with fast charging demand can be scheduled to get charged in an optimal fast charging station.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com