Tutorial

Learn the library step by step. Each page builds on the previous one, and every block of code runs.

Step	You learn
Problem and direction	describe what you want to solve, and minimize or maximize
Constraints	reject, repair or penalize infeasible solutions
Stopping	iterations, evaluations, time and target stops
Operators	how neighborhoods, selection, crossover and mutation plug in
Genetic Algorithm	population-based search
Simulated Annealing	single-trajectory search
Artificial Bee Colony	population search with a single persistence knob
Results and history	read the result and plot convergence
Reproducibility	get the same run twice

Tip

In a hurry? The worked examples solve Knapsack and TSP start to finish.