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摘要:
The teaching–learning-based optimisation (TLBO) algorithm is a population-based metaheuristic inspired on the teaching–learning process observed in a classroom. It has been successfully used in a wide range of applications. In this study, the authors present a variant version of TLBO. In the proposed version, different weights are assigned to students during the student phase, with higher weights being assigned to students with better solutions. Three different approaches to assign weights are investigated. Numerical experiments with benchmark instances of the flow-shop and the job-shop scheduling problems are carried out to investigate the performance of the proposed approaches. They compare the proposed approaches with the original TLBO algorithm and with two variants of TLBOs proposed in the literature in terms of solution quality, convergence speed and simulation time. The results obtained by the application of a Friedman statistical test showed that the proposed approaches outperformed the original version of TLBO in terms of convergence, with no significant losses in the average makespan. The additional simulation time required by the proposed approaches is small. The best performance was achieved with the approach of assigning a fixed weight to half the students with the best solutions and assigning zero to other students.
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篇名 TLBO with variable weights applied to shop scheduling problems
来源期刊 智能技术学报 学科 社会科学
关键词 TLBO VARIABLE WEIGHTS SHOP SCHEDULING PROBLEMS
年,卷(期) 2019,(3) 所属期刊栏目
研究方向 页码范围 148-158
页数 11页 分类号 G
字数 语种
DOI
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研究主题发展历程
节点文献
TLBO
VARIABLE
WEIGHTS
SHOP
SCHEDULING
PROBLEMS
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
智能技术学报
季刊
2468-2322
重庆市巴南区红光大道69号
出版文献量(篇)
142
总下载数(次)
4
总被引数(次)
0
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