作业车间动态调度的综合路由黄蜂算法和调度黄蜂算法

Yan Cao, Yanli Yang, Huamin Wang
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引用次数: 6

摘要

动态调度算法由于在面对突发事件时具有良好的鲁棒性和较高的调度性能而受到越来越多的关注。蜂群算法是一种基于自然昆虫社会行为模型的动态调度算法。基于蜂群算法的原理,结合两种不同的算法,即路由黄蜂算法和调度黄蜂算法来解决作业车间的动态调度问题。对算法进行了改进,以更好地适应作业车间动态调度环境。算法是基于Eclipse 3.2和J2SE 6.0开发的。完成了仿真实验,并对实验数据进行了分析。结果表明,该算法原理简单,计算量小,具有良好的应用前景,适用于进入时间不可预测的多批动态调度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated Routing Wasp Algorithm and Scheduling Wasp Algorithm for Job Shop Dynamic Scheduling
Dynamic scheduling algorithms are gaining more and more special attention for their satisfying robustness when confronted with unexpected events as well as their considerably high performance in scheduling. The wasp colony algorithm is a newly presented dynamic scheduling algorithm, which bases on natural insect society behavior models. Based on the principle of the wasp colony algorithm, two different algorithms, namely the routing wasp algorithm and the scheduling wasp algorithm, are combined to solve the job shop dynamic scheduling problem. The algorithms are modified to better adapt to job shop dynamic scheduling environment. The algorithms are developed based on Eclipse 3.2 and J2SE 6.0. Simulation experiments are accomplished and experimental data are analyzed. The results show that the principle of the algorithms is simple, their computational quantity is small, and they can be applied to multi-batch dynamic scheduling with unpredictable entry time due to their favorable potential.
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