route-mapper's Introduction

OC Transpo network in social network theory

To run the application, open the directory with this project and run `python main.py`

NOTE:

You must have python installed to run
Once you run it will save the graphs in the graphs directory
for line graphs, it will be saved under graphs/line
for the other graphs they will be saved under graphs/[insert bus name]

Libraries used:

matplotlib.pyplot
networkx
random
json
pandas
datetime
uuid
math
pyvis

route-mapper's People

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route-mapper's Issues

graphs to create

Nash Equilibrium for each company priority
shortest path (Nash Equilibrium) effect on passengers
shortest path (Nash Equilibrium) effect on profit
shortest path (Nash Equilibrium) effect on bus capacity (are busses full) (goes hand-in-hand with passenger effect)
shortest path (Nash Equilibrium) effect on travel cost
road network (display nodes and passengers at nodes)
potentially display bus routes?

company priorities:

company priority of passengers: we try to get all passengers in the network (maybe we add busses if we need to)
company priority of profit: get the most passengers in the network using the least amount of busses (i.e pick up most passengers at each stop then take the shortest path to the next node)
company priority of travel cost (speed): pickup passengers and reach the destinations the fastest (i.e pick up passengers going closest to final destination at each node it stops at)

for each company priority we need to generate a graph that shows how:

travel cost was affected
passenger/bus capacity was affected
how profit was affected

revise dijkstra for mandatory node

Create road & bus network

create the real-world road & bus network in python to be used by the application

Create Nash Equilibrium for each Company Priority

Create variation for each priority of the company in charge of busses

company priority of passengers: we try to get all passengers in the network (maybe we add busses if we need to)
company priority of profit: get the most passengers in the network using the least amount of busses (i.e pick up most passengers at each stop then take the shortest path to the next node)
company priority of travel cost (speed): pickup passengers and reach the destinations the fastest (i.e pick up passengers going closest to final destination at each node it stops at)