Inspiration
The 123Loadboard sponsor challenge seemed interesting, and it could potentially be a very useful tool to the trucking industry. Truckers are essential for the everyday goods that we buy. By making their work more efficient and profitable, everyone will be better off. I felt that this was something achievable, even if I did not find the most optimal solution.
What it does
It generates an optimal trip routing for a trucker composed of loads based on available loads from a JSON file database. It tries to maximize profit while accounting for gains, fuel and deadhead costs, time constraints, travel time, and origin location.
How I built it
I wrote pseudocode and planned out how to solve the challenge. I researched optimization algorithms. I ended up implementing a greedy algorithm in Java.
Challenges I ran into
I ran into challenges at every step, including dealing with JSON files, time and dates, optimization, debugging with so much data, and Github. This was also one of my first hackathons and I have very limited experience. I have pretty much no knowledge of optimization, algorithms, and graphs.
Accomplishments that I'm proud of
Completing a challenge and hackathon project alone. The project is functional even though it is may not give the most optimal solution. It took a lot of effort and research to get this up and running.
What I learned
Parsing and writing JSON files, optimization algorithms, annoyances of Java
What's next for Smart Trucker
I want to try to implement better optimization algorithms to get better results more efficiently. I hope to also implement an AI solution as well as a route visualizer on a maps API.
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