Use genetic algorithms to solve the multi-objective scheduling problem.
Set the parameters:
• population_size: the size of population
• crossover_rate: mating rate
• mutation_rate: mutation rate
• mutation_selection_rate: mutation selection rate
• num_iteration: number of iterations
After the setting is completed, it can be executed.
After execution, you can see the Gantt chart results using genetic algorithm.
Price: Welcome to contact us for a quote.
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