多目标置换流水车间问题的改进HLO算法
Improved HLO Method for Multi-objective Flow-shop Scheduling Problem
吴晔1
作者信息
- 1. 中国电子系统工程第四建设有限公司,上海 200051
- 折叠
摘要
置换流水车间调度问题(Flow-shop Scheduling Problem)是生产调度问题的一个子问题,是NP-hard组合优化离散问题之一,具有很强的实际研究意义.在现代的生产制造过程中,单一的目标优化已经满足不了日益发展的工业需求,所以对多目标流水车间调度问题的研究显得尤为重要,已在实际生产中得到广泛应用.在人类学习优化算法HLO的基础上,设计了一种多目标进化算法离散多目标人类学习优化MOHLO以求解该问题,用 MATLAB 编程实现该算法并对几个标准多目标flowshop算例进行仿真测试.实验结果表明,提出的算法比已有的NSGA-Ⅱ算法具有更好的优化性能.
Abstract
Multi-objective flow-shop scheduling problem is a sub problem of production scheduling problem.It is one of the discrete problems of NP-hard optimization and has strong theoretical and actual purpose.In the modern production and manufacturing process,single-objective optimization can't meet the growing industrial demand,so the research on the scheduling problem of multi-objective flow-shop is particularly important.This paper designs a multi-objective evolutionary al-gorithm based on the HLO to solve this problem.It was implemented by MATLAB and simulation on a kind of benchmark functions.The experimental results show that the proposed algorithm has a better optimization performance than the NSGA-Ⅱ.
关键词
多目标flowshop问题/HLO算法/NSGA-ⅡKey words
multi-objective flow-shop scheduling problem/MOHLO/NSGA-Ⅱ引用本文复制引用
出版年
2024
NETL
NSTL
万方数据