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A framework to create road network data to find the optimal set of routes in vehicle routing problem using VeroViz

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Vehicle Route optimization using Veroviz

Travelling Salesman Problem using nearest neighbour and simulated annealing heurisitcs

The function solveTSP_SA accepts 3 inputs:

  1. nodesDF: A VeRoViz nodes dataframe containing n locations, numbered 1 to n. Location 1 is assumed as the home location.

VeRoViz is an open-source project from the Optimator Lab, in the University at Buffalo's Department of Industrial & Systems Engineering The aim of VeRoViz is to help users to obtain road network data, sketch the locations of nodes (e.g. customers and depots), visualize arcs (connections) among these nodes, generate 3D movies show casing solutions to vehicle routing problems, quickly generate test problems and distance (and/or time) matrices.

  1. costDict – A VeRoViz “time” dictionary describing either the travel time, in seconds, from each node to every other node. The contents of costDict will be generated by the VeRoViz getTimeDist2D() function which is an input to our function and this there is no need to calculate this dictionary. The travel time values will be generated using the “ORS-online” dataProvider. Documentation on the “time” dictionary may be found at https://veroviz.org/docs/veroviz.getTimeDist2D.html.

Documentationonthe“ORS-online”dataprovidermaybefoundathttps://veroviz. org/docs/dataproviders.html.

  1. timeLimit – A scalar value describing the maximum runtime of your heuristic, in units of seconds The solveTSP_SA returns a VeRoViz “assignments” dataframe, as described here: https://veroviz.org/docs/assignments.html

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A framework to create road network data to find the optimal set of routes in vehicle routing problem using VeroViz

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