Abstract
In this article, a genetic algorithm is applied for the job scheduling problem in metallurgical equipment manufacturing workshops. The chromosome is divided into two parts, which are the selection of machines and the sequencing of operations. In the machine selection part, uniform crossover and uniform mutation methods are used. While the order-based crossover and exchange mutation methods are adopted in the operations sequencing part. The fitness function is set to be the reciprocal of the maximum completion time. The offsprings are selected through roulette wheel selection until the iteration ends. Finally, we applied the algorithm on the metallurgical equipment manufacturing workshop and the efficiency had been proved.
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Special thanks to Professor Yu Zheng, for the guidance in writing this article.
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Ruan, C., Le, X., Zheng, Y. (2024). Research on Job Scheduling Method for Metallurgical Equipment Manufacturing Workshop Based on Genetic Algorithm. In: Le, X., Zhang, Z. (eds) Advances in Neural Networks – ISNN 2024. ISNN 2024. Lecture Notes in Computer Science, vol 14827. Springer, Singapore. https://doi.org/10.1007/978-981-97-4399-5_53
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DOI: https://doi.org/10.1007/978-981-97-4399-5_53
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