基于改进鲸鱼优化算法的AGV柔性作业车间多目标优化调度*

doi:10.16731/j.cnki.1671-3133.2024.07.003

现代制造工程 ›› 2024, Vol. 526 ›› Issue (7): 17-25.doi: 10.16731/j.cnki.1671-3133.2024.07.003

• 先进制造系统管理运作 • 上一篇下一篇

基于改进鲸鱼优化算法的AGV柔性作业车间多目标优化调度^*

王赟¹, 马荣², 唐思源³

1 山西职业技术学院人工智能系,太原 030006;
2 北京师范大学人工智能学院,北京 100875;
3 内蒙古科技大学包头医学院,包头 014040

收稿日期:2023-09-04 出版日期:2024-07-18 发布日期:2024-07-30
通讯作者: 唐思源,硕士,教授,主要研究方向为计算机应用、图像处理。E-mail:tangsiyuan2023@163.com
作者简介:王赟,硕士,副教授,主要研究方向为生产车间调度、计算机仿真。
基金资助:
*国家自然科学基金项目(10971243);山西省教育科学“十四五”规划2022年度课题项目(GH-220678);内蒙古自治区卫生委员会项目(202201395);包头市卫生健康科技计划项目(wsjkkj2022120)

An IWOA for multi-objective optimization scheduling of AGV flexible job shop

WANG Yun¹, MA Rong², TANG Siyuan³

1 Department of Artificial Intelligence,Shanxi Polytechnic College,Taiyuan 030006,China;
2 School of Artificial Intelligence,Beijing Normal University,Beijing 100875,China;
3 School of Baotou Medical College,Inner Mongolia University of Science and Technology, Baotou 014040,China

Received:2023-09-04 Online:2024-07-18 Published:2024-07-30

摘要/Abstract

摘要： 针对柔性作业车间的自动引导车辆(Automated Guided Vehicle,AGV)调度问题,基于可持续视角,考虑车间能耗问题,在机器和AVG数量均存在数量约束的条件下,以最小化最大完工时间、车间能耗和AGV使用数量为优化目标构建可持续柔性车间调度模型。首先,设计一种改进鲸鱼优化算法(Improved Whale Optimization Algorithm,IWOA),在标准的鲸鱼优化算法的基础上引入非线性收敛因子和自适应惯性权重以提升算法的搜索能力和收敛速度;其次,使用模糊隶属度理论构建了损失函数,以获得多目标模型的最优折衷解;最后,基于算例实验验证算法性能。实验结果表明改进鲸鱼优化算法在求解2个算例时均表现出良好的效果,为求解采用AGV运输的可持续柔性作业车间多目标优化调度提供了一种有效的实践途径。

关键词: 柔性作业车间, 可持续, 多目标优化调度, 改进鲸鱼优化算法, 模糊隶属度

Abstract: Aiming at the problem of Automated Guided Vehicle (AGV) scheduling in flexible job shop,based on the sustainable perspective,considering the problem of workshop energy consumption,under the condition of the number of machines and AVG,a sustainable flexible job shop scheduling model is constructed with the optimization objectives of minimizing the maximum completion time,workshop energy consumption and the number of AGV used.Firstly,an Improved Whale Optimization Algorithm (IWOA) was designed,which introduced a nonlinear convergence factor and adaptive inertia weight on the basis of the standard whale optimization algorithm to improve the search ability and convergence speed of the algorithm.Secondly,the fuzzy membership theory was used to construct the loss function to obtain the optimal compromise solution of the multi-objective model. Finally,the performance of the algorithm was verified based on examples. The experimental results show that IWOA shows good effects in solving instances of different sizes,which provides an effective practical way for solving the sustainable flexible job shop optimization scheduling with AGV transportation.

Key words: flexible job shop, sustainable, multi-objective optimization scheduling, Improved Whale Optimization Algorithm (IWOA), fuzzy membership

中图分类号:

TH165
TP18

王赟, 马荣, 唐思源. 基于改进鲸鱼优化算法的AGV柔性作业车间多目标优化调度^*[J]. 现代制造工程, 2024, 526(7): 17-25.

WANG Yun, MA Rong, TANG Siyuan. An IWOA for multi-objective optimization scheduling of AGV flexible job shop[J]. Modern Manufacturing Engineering, 2024, 526(7): 17-25.

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基于改进鲸鱼优化算法的AGV柔性作业车间多目标优化调度^*

An IWOA for multi-objective optimization scheduling of AGV flexible job shop

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