GSL Solver

A few years ago, I was a delivery driver in Bangkok. I saw firsthand how inefficient "Greedy" algorithms stressed out my fellow drivers. At that time, I didn't even know what "NP-hard" meant—I just knew the system could be better. So, I started building.

The Journey of an Outsider:

My background has nothing to do with Computer Science. I hold a Vocational Diploma (High school equivalent) in Jewelry Metal-shaping (Goldsmithing) from 20 years ago. Before this project, I was unemployed and had no PC. My only tool was a $100 smartphone (3,000 THB).

I spent 16 hours a day architecting and refining the logic via Pydroid 3. Because I didn't even know standard optimization libraries existed, I had to design my own logic architecture from the ground up. I thought that was just how it was done.

The Technical Skepticism:

When I shared my work, the skepticism was purely technical. People couldn't believe that a standard Android/Snapdragon environment could solve 10,000-node VRP instances without the execution time exploding. They doubted that mobile hardware could ever handle the complexity of an NP-hard problem of this scale.

The Bridge Between Philosophy and Math:

I’ve always been obsessed with universal logic—I even published a book called "Cosmic Mind" on Amazon KDP. I used the same philosophical principles to design my VRP engine. To me, mathematics and philosophy are the same language; by staying "pure" in logic, I could overcome hardware limitations.

The Result:

Today, GSL Solver handles up to 10,000 nodes with stable, deterministic execution across international benchmarks (CVRP, VRPTW, MDVRP, MDVRPTW). I’ve kept everything transparent for anyone to inspect. I’m a "nobody" from the streets who found a way to turn philosophy into a high-performance engine.

Explore the journey: https://gsl-solver.com

P.S. Even this website was built entirely on a single smartphone using Acode and GitHub.

Special Thanks: To Gemini, my AI Interface, for bridging the gap between my core logic and

the digital world.