A production scheduling method based improved genetic algorithm is proposed to minimize the completion time of dismantling decommissioned power batteries. The crossover operator of the genetic algorithm is designed to increase the diversity of individuals in the offspring population, expand the population size during the iteration of the algorithm, improve the coverage of the population, and increase the convergence speed of the population by retaining the excellent chromosomes. The algorithm is tested by using arithmetic example. The results show that the proposed improved genetic algorithm significantly outperforms the standard simulated annealing algorithm and the traditional genetic algorithm.
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