[1]姚 雄,张永平.求解作业车间调度问题的离散海洋捕食者算法[J].机械与电子,2022,(12):24-29.
　YAO Xiong,ZHANG Yongping.Discrete Marine Predators Algorithm for Solving Job Shop Scheduling Problem[J].Machinery & Electronics,2022,(12):24-29.
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求解作业车间调度问题的离散海洋捕食者算法()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2022年12期
页码:
24-29
栏目:
设计与研究
出版日期:
2022-12-24

文章信息/Info

Title:
Discrete Marine Predators Algorithm for Solving Job Shop Scheduling Problem
文章编号:
1001-2257 ( 2022 ) 12-0024-06
作者:
姚 雄 1 ; 张永平 2
1. 盐城工学院机械工程学院,江苏 盐城 224051 ; 2. 盐城工学院信息工程学院,江苏 盐城 224051
Author(s):
YAO Xiong1 ;  ZHANG Yongping2
( 1.School of Mechanical Engineering , Yancheng Institute of Technology , Yancheng 224051 , China ; 2.School of Information Engineering , Yancheng Institute of Technology , Yancheng 224051 , China )
关键词:
作业车间调度问题; 海洋捕食者算法; 混沌映射; 对立学习
Keywords:
job shop scheduling ;  marine predators algorithm ;  chaotic mapping ;  opposition-based learning
分类号:
TP391.4
文献标志码:
A
摘要:
为把海洋捕食者算法应用于作业车间调度问题,提出了离散海洋捕食者算法。首先,对原算法的连续位置向量进行了离散转换。其次,使用对立学习方法增加初始种群的多样性;采用圆形混沌映射函数来提高算法的收敛速度;改进自适应步长策略从而更好地平衡勘探和开发。最后,通过对典型调度基准算例的测试,并同其他算法进行对比,验证了离散海洋捕食者算法在求解作业车间调度问题时的有效性及更优良的算法特性。
Abstract:
In order to apply the marine predator algorithm to the job shop scheduling problem , a discrete marine predators algorithm is proposed.Firstly , the continuous position vector of the original algorithm is discretely transformed.Secondly , the algorithm uses opposition-based learning to increase population diversity in the population initialization stage ; the algorithm uses the circle map chaotic mapping function to improve the convergence speed of the algorithm ; the algorithm uses an improved adaptive step size strategy to better balance exploration and exploitation.Finally , the algorithm selects basic examples to test the performance of the algorithm , and compared with other metaheuristic algorithms , the effectiveness and superiority of discrete marine predators algorithm are verified in solving job shop scheduling problem.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2022-06-03
基金项目:江苏省产学研合作项目( BY2022502 )作者简介:姚 雄 ( 1992- ),男,江苏南京人,硕士研究生,研究方向为智能化设计理论与技术、智能算法、生产调度;张永平 ( 1979- ),男,河北邯郸人,博士,副教授,硕士研究生导师,研究方向为大数据技术、人工智能和压缩感知等。
更新日期/Last Update: 2023-01-05