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GIF
An early version of the path finding system - together with multiple cars
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GIF
Multiple cars serve multiple persons -> path highlighting buggy
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Early attempts to modle that problem -> oups it was harder than expected
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Early attempts to simplify graph using a shortest Dijkstra paths to simplify the traveling sales person problem => Minimal Spanning Tree
Inspiration
Sixt new taxi service! It creates interesting problems about how to distribute your resources effectively We sought to create a fleet management system, that would optimally use the fleet's resources. We wanted to take into account the possibility of carsharing, the current batterystatus of any given vehicle. to help with understanding of the current traffic, we created a visualization tool, by translating points of interest into a graph. With the given graph, we could then implement Dijkstra's algorithm to calculate the shortest path. This system could be used in combination with the api to simulate orders and vehicles as objects.
What it does
It simulates a town with people that book sixt taxis and calculates optimal paths to reduce pollution and costs
How we built it
We used normal c# to create a model, which then can be visualized with the unity3d
Challenges we ran into
TSP, Dijkstra and formulating the problem
Accomplishments that we're proud of
We've created a city that automatically creates and assigned bookings to simulate the pick up process of taxis and customers. We've visualized the process
What we learned
A lot about the TSP complexity, Implementing efficient dijkstra =>.net 5 doesn't have a priority queue => thanks for that... And getting better at problem-solving
What's next for Sixt Taxi Distributer Optimizer
Creating more complex environments to see if our algorithms can withstand that and creating better visuals Also taking the following things into account! => Charge status => Charge stations => Traffic => Traveling Sales Person Problem Problem => Comparison between different optimization alogrithms
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