Automatic algorithm design for multi-objective hybrid flowshop scheduling problem with variable sublots

被引：0
|
作者：
Zhang B. [1 ]
Meng L. [1 ]
Sang H. [1 ]
Lu C. [2 ]
机构：
[1] School of Computer Science, Liaocheng University, Liaocheng
[2] School of Computer Science, China University of Geosciences, Wuhan
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 11期
关键词：
automatic algorithm design; hybrid flowshop scheduling; multi-objective evolutionary algorithm; variable sublots;
D O I：
10.13196/j.cims.2022.11.007
中图分类号：
学科分类号：
摘要：
With the consideration of setup and transportation operations,the multi-objective hybrid flowshop scheduling problem with variable sublots was studied,which was aimed to simultaneously optimize two conflicting objectives ：the makespan and the total number of sublots. A multi-objective mixed integer programming model was developed and the trade-off between the two objectives was evaluated. Since the problem belongs to Non-deterministic Polynomial (NP) problems,the Multi-objective Evolutionary Algorithm (MOEA) was suggested to solve it. To e-liminate the biases of previous experience for configuring MOEA, an Automated Algorithm Design (AAD) methodology was introduced to conceive a promising MOEA based on MOEA framework,which was enabled designing the MOEA by determining parameters and their combinations automatically with minimal user intervention. Considering the variable sublots,a dynamic decoding strategy was proposed. With regards to the problem-specific characteristics and the employed algorithm framework,for the categorical and numerical parameters,reasonable value ranges were given. For the AAD methodology,the I/F-Race was employed. Compared with CPLEX,the automated MOEA was demonstrated much more effective. © 2022 CIMS. All rights reserved.
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页码：3403 / 3420
页数：17
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