Genetic Algorithm (GA) for combinatorial and discrete optimization problems. Inspired by biological evolution with sele…
Genetic Algorithm (GA) for combinatorial and discrete optimization problems. Inspired by biological evolution with selection, crossover, mutation, and elitism. Foundation for NSGA-II multi-objective optimization. Best for TSP, scheduling, assignment problems in MCM/ICM.
spiral-edwin
cli
free
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