首页|改进算术优化算法求解考虑机器老化效应和工件释放时间的作业车间调度问题

改进算术优化算法求解考虑机器老化效应和工件释放时间的作业车间调度问题

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研究考虑机器具有老化效应和工件带有释放时间约束的作业车间调度问题(job shop-scheduling problem,JSP)。建立以最小化最大完工时间为目标的调度优化模型,并设计1种改进的算术优化算法(improved arithmetic optimization algorithm,IAOA)对该问题进行求解。算法首先通过排序值转换规则将IAOA连续解空间映射到JSP的离散空间,并对JSP进行编码,然后使用插入式贪婪解码算法进行解码。提出了非线性数学优化加速函数和6种邻域搜索策略对标准算术优化算法(arithmetic optimization algorithm,AOA)进行改进。通过在33个JSP数据集上进行测试并与AOA、灰狼优化算法和算术三角函数优化算法进行对比分析,结果表明提出的IAOA具有较好的优化效果以及收敛能力,且该算法克服了 AOA求解精度低、收敛速度慢的缺陷。
Improved Arithmetic Optimization Algorithm for Solving Job Shop-Scheduling Problems with Machine Aging Effects and Workpiece Release Time
The Job Shop-Scheduling Problem(JSP),which considers the constraints of machines with aging effects and workpieces with release time,is studied.A scheduling optimization model with the objective of minimizing the maximum completion time is developed and an improved Arithmetic Optimization Algorithm(IAOA)is designed to solve the problem.The algorithm maps the IAOA continuous solution space to the discrete space of the JSP by means of ranked-order value(ROV)transformation rules,encodes the JSP and decodes it using an insertion greedy decoding algorithm.A non-linear mathematical optimization acceleration(MOA)function and six neighborhood search strategies are proposed to improve the standard Arithmetic Optimization Algorithm(AOA).The IAOA is compared with AOA,Grey Wolf Optimizer(GWO)and Arithmetic Trigonometric Optimization Algorithm(ATOA)by solving 33 benchmark problems.The experimental results show that the IAOA proposed has better optimization effect and convergence ability on JSP.The IAOA algorithm proposed overcomes the shortcomings of the AOA algorithm in terms of low solution accuracy and slow convergence speed.

arithmetic optimization algorithmjob-shop scheduling problemsinsertion greedy decoding algorithmmachine aging effectrelease time

陈照辉、刘海杨、夏倩、张新功

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重庆科技大学数理与大数据学院

重庆科技大学智能技术与工程学院,重庆 401331

重庆谢家湾学校,重庆 400050

重庆师范大学数学科学学院,重庆 401331

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算术优化算法 作业车间调度问题 插入式贪婪解码算法 机器老化效应 释放时间

国家自然科学基金——重大项目国家自然科学基金——面上项目重庆市自然科学基金重庆市教育委员会科学技术研究计划——重点项目重庆市教育委员会科学技术研究计划——重点项目重庆市教育委员会科学技术研究计划——青年项目

1199102211971443cstc2021jcyjmsxmX0229KJZD-K202000501KJZD-K202301502KJQN202001507

2024

重庆师范大学学报(自然科学版)
重庆师范大学

重庆师范大学学报(自然科学版)

CSTPCD北大核心
影响因子:0.652
ISSN:1672-6693
年,卷(期):2024.41(2)
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