基于遗传算法的预制件生产调度

W. Chan, H. Hu
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引用次数: 5

摘要

针对专业化预制件生产调度难题,提出了一种结合实际约束条件的流程车间排序模型。采用遗传算法对模型进行求解。对传统的最小化完工时间目标函数和更实用的最小化延误惩罚目标函数分别进行优化,并采用加权方法同时进行优化。实验研究了增加种群规模和用启发式解播种初始种群的效果。遗传算法与经典启发式规则的比较表明,在发现一组好的解方面,遗传算法即使不比启发式规则更好,也是竞争性的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precast production scheduling with genetic algorithms
A flow shop sequencing model (FSSM) that incorporates actual constraints encountered in practice is proposed for the difficult case of specialized precast production scheduling. The model is solved using a genetic algorithm (GA). The traditional minimize makespan and the more practical minimize tardiness penalty objective functions are optimized separately, as well as simultaneously using a weighted approach. Experiments are conducted to investigate the effect of increasing population size and seeding the initial population with heuristic solutions. Comparisons between the GA and classical heuristic rules show that the GA is competitive, if not better than heuristic rules in discovering a set of good solutions.
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