基于总设置时间与最大完工时间的柔性流水车间多目标优化研究OA北大核心CSTPCD
Multi-objective Optimization of Flexible Flow Shop Based on the Total Setup Time and the Makespan
本课题以最大完工时间及总设置时间为优化目标,提出了一种新的解码方案,并设计了混合快速非支配遗传算法,用于求解建立的生产调度模型,通过实验证明了模型的有效性及算法的先进性.结果表明,提出的解码方案最大可减少25.63％的总设置时间及3.42％的最大完工时间;混合快速非支配遗传算法则最大可减少28.42％的总设置时间及3.80％的最大完工时间.
Taking the makespan and total setup time as the optimization objectives,a new decoding scheme was created and a hybrid fast non-dominated genetic algorithm was designed to solve the established production scheduling model.Based on the experiments results,the effec-tiveness of the model and the advancement of the algorithm were carried out.The results showed that proposed decoding scheme could reduce the total setup time by 25.63％and the makespan by 3.42％.The hybrid fast non-dominated genetic algorithm could reduce the total setup time by 28.42％and the makespan by 3.80％.
曾志强;蔡文青
五邑大学智能制造学部,广东江门,529020
轻工业
生产调度柔性流水车间多目标优化
production schedulingflexible flow shopmulti-objective optimization
《中国造纸学报》 2024 (001)
82-90 / 9
广东省基础与应用基础研究基金(2020A1515011468);广东省普通高校特色创新类项目(2019KTSCX189).
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