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Flexible integrated scheduling algorithm based on remaining work probability selection coding

Aiming at the integrated scheduling problem of tree‐structured products with flexible machine selection, this article proposes a flexible integrated scheduling algorithm based on remaining work probability selection coding. The algorithm is based on the framework of a genetic algorithm. First, in order to ensure the diversity and goodness of the initial population, an encoding method based on remaining work probability selection is proposed. Second, two new different crossover and mutation methods are designed based on operation and position respectively, which ensure the legitimacy of the generated offspring individuals. Then, in order to enhance the searchability of the algorithm for an optimal solution of the problem, a local search strategy based on the machine is proposed. Finally, a simple and effective decoding method based on the idle period is given. The algorithm is tested by the existing instance and randomly generated instances. The experimental results show that the proposed algorithm's solving speed and solution quality outperform other comparison algorithms.