Advanced transportation optimization problem

Question

I'm trying to explore OR problems and wanted to know what algorithm fits here.

Consider fuel stations with lithium ion battery that service replacing battery at each refuel ( you replace your batters with a new one). As an optimization problem, I'd like to identify warehouses (that have some capacity storage of battery quantity) and connect to these fuel stations such that all fuel stations run at least with 50% capacity. An added constraint is that we need to ensure the distance is less than 50 miles from the warehouses.

I'm looking to seek help on what optimization problem for this situation.

Example -

distance_df= [{'Fuel Station':'FS1', 'Warehouse1': 40, 'Warehouse2': 38, 'Warehouse3':68},
    {'Fuel Station':'FS2', 'Warehouse1':53, 'Warehouse2': 46, 'Warehouse3': 50},
    {'Fuel Station':'FS3', 'Warehouse1':62, 'Warehouse2': 80, 'Warehouse3': np.nan},
    {'Fuel Station':'FS4', 'Warehouse1':75, 'Warehouse2': np.nan, 'Warehouse3': 50}]

capacity_df = [{'Warehouse':'Warehouse1', 'Capacity': 2500},
    {'Warehouse':'Warehouse2', 'Capacity':2000},
    {'Warehouse':'Warehouse3', 'Capacity':3200}]

demand_df = [{'Fuel Station':'FS1', 'Demand': 2300},
    {'Fuel Station':'FS2', 'Demand':4680},
    {'Fuel Station':'FS3', 'Demand':8000}]

Basically I'm looking to find the optimal setting such that all fuel stations are met 50% of their demand and within 50 miles from the connected warehouse.

There is no [tag:python] in this question. See [ask] and how to create a [mcve]. — Peter Wood, Aug 28 '21 at 19:41
https://docs.scipy.org/doc/scipy/reference/optimize.linprog-simplex.html — Peter Wood, Aug 28 '21 at 19:42
The first thing to do is to write down the mathematical model for the problem. After that it is easier to choose a solution strategy. — Erwin Kalvelagen, Aug 28 '21 at 23:19
Please provide enough code so others can better understand or reproduce the problem. — Community, Aug 30 '21 at 20:13

Advanced transportation optimization problem

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