Sun N, Cao B. Production Scheduling Optimization of Garment Intelligent Manufacturing System Based on Big Data.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022;
2022:2293473. [PMID:
36045981 PMCID:
PMC9420574 DOI:
10.1155/2022/2293473]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 07/21/2022] [Accepted: 07/22/2022] [Indexed: 11/25/2022]
Abstract
In order to improve the efficiency of cloth laying and cutting integrated production process, this article proposes a method of optimal scheduling of cloth laying and cutting garment production system process based on big data and genetic algorithm. The chromosomes in the algorithm are expressed by real strings. The method of bit string crossover and mutation is used to solve the premature problem of the algorithm. The experimental results show that the actual cutting time of the plan is 736 min, and the total idle time is 113 min. The idle time occurs in processes 25, 28, 34, 35, and 31, respectively. The cutting time of the plan arranged by the genetic algorithm is 627 min, and there is no idle time. Conclusion. This method can effectively solve the optimal scheduling problem of the cloth laying and cutting production process.
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