Re: [datameet] Routing challenge: Covery every path optimally

https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.euler.eulerize.html Essentially you need eulerize the subgraph and then find a Euler circuit. The circuit is the route each surveyor needs to take. Both of them are linear time algorithms. best,    

Re: [datameet] Routing challenge: Covery every path optimally

after the partitions, you can use https://github.com/brooksandrew/postman_problems best,     Dilawar -- Datameet is a community of Data Science enthusiasts in India. Know more about us by visiting http://datameet.org --- You received this message because you are subscribed to the Google

Re: [datameet] Routing challenge: Covery every path optimally

Thank you Julien, Ujaval, Dilawar for your excellent responses. It's a relief to learn that this is not one of those "will take ages to compute" ones. Fascinating, but still hauntingly just beyond my technical reach. Dilawar : talk is cheap : Agreed! Here's some sample data:

Re: [datameet] Routing challenge: Covery every path optimally

Solutions to such problems can be found in operational research literature. Have a look at min-flow max-cut problems in graph theory which are suited to solve this kind of optimization problem (

Re: [datameet] Routing challenge: Covery every path optimally

A colleague of mine solved a similar problem using the OpenRouteService API. They used k-means clusters to determine the initial distribution of points between surveyors and the optimization API for solving optimal routing between the

[datameet] Routing challenge: Covery every path optimally

Hi All, Wishing everyone good health, stability and pragmatism in these times. I came across a certain technical problem statement pertaining to ground survey planning in a target area: Given X ground surveyors, Create X routes that start from one location, Cover all the existing roads and