基于多目标海鸥算法的分布式焊接节能调度

doi:10.3901/JME.2024.22.192

机械工程学报 ›› 2024, Vol. 60 ›› Issue (22): 192-203.doi: 10.3901/JME.2024.22.192

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基于多目标海鸥算法的分布式焊接节能调度

卢超¹, 田禾子¹, 李新宇², 张彪

1. 中国地质大学(武汉)计算机学院武汉 430074;
2. 华中科技大学智能制造装备与技术国家重点实验室武汉 430074;
3. 聊城大学计算机学院聊城 252000

收稿日期:2023-11-25 修回日期:2024-06-20 出版日期:2024-11-20 发布日期:2025-01-02
作者简介:卢超,男,1986年出生,博士,副教授。主要研究方向为智能生产调度。E-mail:luchao@cug.edu.cn;田禾子,男,1995年出生。主要研究方向为智能车间调度。E-mail:tianhezi@cug.edu.cn;李新宇(通信作者),男,1985年出生,博士,教授,博士研究生导师。主要研究方向为智能生产调度。E-mail:lixinyu@mail.hust.edu.cn;张彪,男,1990年出生,博士,讲师,硕士研究生导师。主要研究方向为机器学习与智能优化。E-mail:zhangbiao@lcu-cs.com
基金资助:
国家自然科学基金资助项目(52175490，51805495)。

Energy-efficient Distributed Welding Shop Scheduling Based on Multi-objective Seagull Algorithm

LU Chao¹, TIAN Hezi¹, LI Xinyu², ZHANG Biao

1. School of Computer Science, China University of Geosciences, Wuhan 430074;
2. State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong Universityof Science and Technology, Wuhan 430074;
3. School of Computer Science and Technology, Liaocheng University, Liaocheng 252000

Received:2023-11-25 Revised:2024-06-20 Online:2024-11-20 Published:2025-01-02
About author:10.3901/JME.2024.22.192

摘要/Abstract

摘要： 针对分布式焊接节能调度问题，以分布式焊接车间调度生产为研究对象，建立以最小化最大完工时间和总能耗为目标的数学模型。为了求解该优化问题，提出一种改进的多目标海鸥算法。在此算法中主要改进了以下三点：设计一种基于多关键路径的权值矩阵，用于更新每个工件分配的焊机数量；根据分布式焊接车间的特点重新设计了多目标海鸥算法的离散化操作；引入一种帕累托前沿选择策略。这些改进方法不仅减少了最大完工时间与总耗能，同时也提高了搜索效率。最后，改进的海鸥算法与其他算法在几种不同规模的案例中进行了对比，试验结果验证了所提算法的优越性。

关键词: 多目标优化, 焊接车间, 节能调度, 关键路径, 离散化

Abstract: For the distributed welding shop scheduling problem, a mathematical model with the objective of minimizing the maximum completion time and total energy consumption is developed. In order to solve this optimization problem, an improved multi-objective seagull algorithm is proposed. The algorithm makes the following three main improvements: A weight matrix based on multiple critical paths is designed to update the number of welders assigned to each job; the discretization operation of the multi-objective seagull algorithm is redesigned according to the characteristics of the distributed welding shop; Pareto front selection strategy is introduced. These improved methods not only reduce the maximum completion time and total energy consumption, but also improve the search efficiency. Finally, the improved seagull algorithm is compared with other algorithms in several cases of different scales, and the experimental results verify the superiority of the proposed algorithm.

Key words: multi-objective optimization, welding shop, energy-efficient scheduling, critical path, discretization

中图分类号:

TG156

卢超, 田禾子, 李新宇, 张彪. 基于多目标海鸥算法的分布式焊接节能调度[J]. 机械工程学报, 2024, 60(22): 192-203.

LU Chao, TIAN Hezi, LI Xinyu, ZHANG Biao. Energy-efficient Distributed Welding Shop Scheduling Based on Multi-objective Seagull Algorithm[J]. Journal of Mechanical Engineering, 2024, 60(22): 192-203.

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基于多目标海鸥算法的分布式焊接节能调度

Energy-efficient Distributed Welding Shop Scheduling Based on Multi-objective Seagull Algorithm

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