Welcome to the repository for my exam project in the course "Machine Intelligence for Combinatorial Optimization." This project delves into various metaheuristic algorithms applied to combinatorial optimization problems. The repository encompasses implementations of algorithms such as Simulated Annealing, Genetic Algorithms, Population Algorithms, among others. Each algorithm has been rigorously tested and evaluated on different benchmark problems to demonstrate their effectiveness and efficiency in finding optimal or near-optimal solutions.
Repository Contents Algorithm Code: Implementations of the studied metaheuristic algorithms in Python. Benchmarks: A collection of optimization problems used to test and assess the performance of the algorithms. Documentation: Detailed descriptions of the methods employed and the conclusions drawn from the results. Thank you for visiting this repository! Should you have any questions or suggestions, please feel free to contact me.