Introducing: RapidSolve - A meta-heuristic library for combinatorial optimization
As part of the Institute for Operations Research at ETH Zurich, I gained extensive experience in solving optimization problems using local search-based meta-heuristics. What started as a hobby project evolved into a library called RapidSolve, which provides a framework for implementing multiple meta-heuristics to tackle combinatorial optimization problems. Over time, we developed and integrated the following algorithms into the library:
- (Parallel/recursive) local search
- Threshold accepting
- Simulated annealing
- (Parallel) tabu search
More to come.
If your goal is to solve a hard optimization problem, and you see a possibility to explore the solution space by applying modification to a given solution, then this library will help you to quickly apply various meta-heuristics without much effort.
Since there is not the >one< algorithm that fits all problems, this is a comfortable way to find the best meta-heuristic for your problem. Give it a try.
Combinatorial optimization is an area where Rust really shines. Previously dominated by C++ more and more research team and companies switch to Rust to write optimization algorithms.