CAJ | 학술논문

针对传统Job-Shop数学模型忽略返工及重加工的因素，构建了考虑该情形下的Job-Shop调度数学模型及相应的求解算法。该模型详细分析了返工及重加工的流程，对问题的定义做了进一步推导，模型以总加权拖期最小为目标，并提出一种改进的遗传算法对该模型进行求解。针对该调度情形，对算法中染色体的编码、种群初始化进行改进。种群数据的仿真实验表明，与传统遗传算法相比，改进后的算法在收敛速度、求出的最小总加权拖期方面均优于前者。最后通过对10×10实例调度方案求解及仿真，并与作业车间实际调度结果比较，模型仿真所得总加权拖期小于实际计划调度结果的46％，本模型得出的调度方案是实用且有效的。
침대전통Job-Shop수학모형홀략반공급중가공적인소，구건료고필해정형하적Job-Shop조도수학모형급상응적구해산법。해모형상세분석료반공급중가공적류정，대문제적정의주료진일보추도，모형이총가권타기최소위목표，병제출일충개진적유전산법대해모형진행구해。침대해조도정형，대산법중염색체적편마、충군초시화진행개진。충군수거적방진실험표명，여전통유전산법상비，개진후적산법재수렴속도、구출적최소총가권타기방면균우우전자。최후통과대10×10실례조도방안구해급방진，병여작업차간실제조도결과비교，모형방진소득총가권타기소우실제계화조도결과적46％，본모형득출적조도방안시실용차유효적。
A Job-Shop scheduling is addressed with the consideration of stochastic rework and reprocessing while the traditional Job-Shop mathematical model ignored it .The objective of the model is to minimize the Total Weighted Tardiness (TWT) in these job shops.To solve the problem, a modified genetic algorithm is proposed with coding and population initialization improved .Five groups of population data for simula-tion experiments show that compared with the traditional genetic algorithm , the improved algorithm is better in convergence speed and the target value of TWT .Finally, through simulating the instances of scheduling scheme , and comparing with the actual Job-Shop scheduling results , the TWT of model simulation is less than 46%of the actual project scheduling results , and the scheduling scheme model proves practical and effective.