[1]郑天华,王佳斌,蔡宇翔,等.应用禁忌粒子群算法的车间调度及其并行化实现[J].华侨大学学报(自然科学版),2023,44(1):104-110.[doi:10.11830/ISSN.1000-5013.202204008]
 ZHENG Tianhua,WANG Jiabin,CAI Yuxiang,et al.Workshop Scheduling Using Forbidden Particle Swarm Algorithm and Its Parallel Implementation[J].Journal of Huaqiao University(Natural Science),2023,44(1):104-110.[doi:10.11830/ISSN.1000-5013.202204008]
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应用禁忌粒子群算法的车间调度及其并行化实现()
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《华侨大学学报(自然科学版)》[ISSN:1000-5013/CN:35-1079/N]

卷:
第44卷
期数:
2023年第1期
页码:
104-110
栏目:
出版日期:
2023-01-10

文章信息/Info

Title:
Workshop Scheduling Using Forbidden Particle Swarm Algorithm and Its Parallel Implementation
文章编号:
1000-5013(2023)01-0104-07
作者:
郑天华 王佳斌 蔡宇翔 彭凯
华侨大学 工学院, 福建 泉州 362021
Author(s):
ZHENG Tianhua WANG Jiabin CAI Yuxiang PENG Kai
College of Engineering, Huaqiao University, Quanzhou 362021, China
关键词:
车间调度 并行化 禁忌粒子群算法 智能算法 Hadoop集群
Keywords:
workshop scheduling parallelization forbidden particle swarm algorithm intelligent algorithm Hadoop colony
分类号:
TP301.6;F406.6
DOI:
10.11830/ISSN.1000-5013.202204008
文献标志码:
A
摘要:
为了解决批量生产、制造、装配等车间调度问题,基于Hadoop集群,提出应用禁忌粒子群算法的车间调度及其并行化实现.以某装载机制造车间最小化完成时间为目标,通过使用禁忌粒子群算法对车间调度问题进行求解.结果表明:在车间批量大的情况下,禁忌粒子群算法可得出有效的调度方案,避免算法陷入局部最优解.与现有的智能算法相比,禁忌粒子群算法更有利于实现全局最优解.
Abstract:
In order to solve the workshop scheduling problems of mass production, manufacturing and assembly, workshop scheduling using forbidden particle swarm algorithm and its parallel implementation is proposed based on Hadoop colony. A loader manufacturing workshop aims to minimize the completion time, the forbidden particle swarm algorithm is used to solve the workshop scheduling problem. The results show that the forbidden particle swarm algorithm can obtained an effective scheduling and avoid the algorithm from falling into a local optimal solution in case of large batch in the workshop. Compared with the existing intelligent algorithms, the forbidden particle swarm algorithm is more beneficial to achieve the global optimal solution.

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备注/Memo

备注/Memo:
收稿日期: 2022-04-08
通信作者: 王佳斌(1974-),男,副教授,主要从事激光应用、嵌入式系统开发、测量技术、智能仪器的研究.E-mail:fatwang@hqu.edu.cn.
基金项目: 国家自然科学基金青年科学基金资助项目(61505059)
更新日期/Last Update: 2023-01-20