Consultation: prediction of each vessel's arrival-departure
data1maths
Member Posts: 27 
Contributor I
Hello everyone,
I realy need your consultation-help in a certain matter.
I intend to accept my participation in a challenging project. This project is made for the purpose of predicting for each vessel the optimal time of arrival and departure, for one aim which is to optimize the overall congestion of vessels inside the port knowing that it has constant capacity and fluctuating demand that depends on many parameters available from many database servers.
I am wondering if ti is doable to create such a Machine learning\Deep learning model (some suggestions\feedback from you would be very helpful and I’ll be grateful)
I did created many ML models(classification-regression-ensembling models-time series analysis(arima-lstm)……) for many projects before, it(s just that I have never face such challenge and I need some guidance from you sepais 
Thank you in advance.
Best regards.
Answers
Hello, @data1maths
That is indeed a very challenging project, I envy you!
I have tried something similar three years ago, and it was also for vessels in a shipyard. You "can" solve it with Machine Learning if you have optimal entries at first but I would refrain from doing so. Don't go unsupervised, that's my best advice here, unless you want to generate a heatmap on how busy is the shipyard, but once you get your segments it is a long way to interpret these correctly so that you can take action. Your problem is pretty much solved by another area of computer science called heuristics, as it is similar (with certain variations) to the solutions given to the problem of classroom assignment. (Check my wording, as I know the name of that problem in Spanish).
You will constantly have a matrix (vessel type, sea level, etc...), and a list of vessels that are heading towards or leaving the shipyard. You can organize a multi-directional cube to select the best combinations of features, and give a vote to them, pondering risks (you don't want to assign a small park to the Titanic, nor try to park the Buque Escuela Esmeralda in a sandy beach). Vessel routes can be calculated by Dijkstra's shortest path algorithm, so that if two routes collide (GIS is your best friend here, so make sure you have a PostgreSQL with PostGIS nearby at any given time) you will have to give priority to the vessel with the largest waiting time to release the pool.
I think your architecture will be very similar to the one I talked about in RapidMiner Wisdom, so here is a tip for you:
You have a long way to go, my friend.
Hope this helps,
Rodrigo.
That's a very deep explanation, surely i'll take in consideration.
I'll keep you in touch about any progress i make.
Thank you so much sir for your help.
Best regards.
Hi,
this sounds also to fit the problems modelled in operation research. Using graph algorithm and eventually simulatios if it becomes too complex, you can come up with a solution.
It is the kind of approach used for example when deciding the schedule for a football liga (for example the Bundesliga). There are several constraints, like that every team plays once home and once away, every team has to play agains all others, there are also other tournaments and matches of the national teams, etc.
Once you get a bit into the topic I'm sure it will become easy, good luck!
Thank you for your reply.
In fact i did studied operations research course, and I tried to model the cost function of this problem at first presuming that it's going to be a linear function and also the constraints functions, yet the model was biased and i couldn't approach the problem using non linear modeling at the time, that why i thought that an ML/DL model could solve this non-linearity issue.
I'll be grateful if you share with me any advice you might think of as being useful to this project.
Thank you.
Best Regards