I'm quite a new programmer and especially to python. So far I'm able to perform basic stuff all related to data analytics and visualization.
This time I'm trying to come up with a model to minimize the leading time of a set of "stations". Let me clarify as I think the idea is simple, the execution though looks (at least to me) more complex. So, let's say that I have 5 stations with workers on everystation, the product starts on station 1 and finishes on station 5. On every station there's a set of activities to be performed, every acitivity having its own duration. A given station starts its activities only when the previous is complete. The station with the maximum duration will be the driving station, i.e.:
Station 1 - 1 min, Station 2 - 1.4 min; Station 3 - 6 min; Station 4 - 1.1 min; Station 5 - 1.5 min
As you can see, the activities on station 4 can only start after 6 minutes, and the total time is 11 minutes. I have the possibility of distributing the activities on station 3 to its neighbours, and thus level the workload across stations.
Is there a way to this with python? I would like to create a program where I give the number of stations, the activities and its duration, some other constraints (like activity x can only happen on station 1) and the output should be the distribution of all activities across all stations with the minimum driving time possible. I don't expect any code of you guys, just some ideas to get me started. I can add any clarification if what I explained it's still confusing. Thanks a lot!