[D] What type of machine learning can be used to solve timetable optimisation problems?

• NLNS

  1 68 1.8 Python

  Neural Large Neighborhood Search for the Capacitated Vehicle Routing Problem

I do not believe anyone has tried ML methods for solving timetable problems yet, so this would be new. My group has come up with several different options for ML+Optimization, but probably our approach "Neural Large Neighborhood Search" will be the most promising here. See our ECAI paper: https://ecai2020.eu/papers/786_paper.pdf, medium post explaining the method: https://dot-bielefeld.medium.com/learning-improvement-heuristics-for-vehicle-routing-problems-with-neural-large-neighborhood-search-6e19252e85f4 and source code: https://github.com/ahottung/NLNS.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

Suggest a related project