A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines-Reference-Cited by-同舟云学术

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A genetic regulatory network based method for multi-objective sequencing problem in mixed-model assembly lines

Published:2019 Issue:3 Volume:16 Page:1228-1243
ISSN:1547-1063
Container-title:Mathematical Biosciences and Engineering
language:en
Short-container-title:

Author:

Lv Youlong, ,Zhang Jie

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modelling and Simulation,General Medicine

Reference5 articles.

1. N. Boysen, M. Fliedner and A. Scholl, Production planning of mixed-model assembly

2. N. Boysen, M. Fliedner and A. Scholl, Sequencing mixed-model assembly

3. U. Golle, F. Rothlauf and N. Boysen, Car sequencing versus mixed-model

4. J. Bautista, R. Alfaro-Pozo and C. Batalla-García, Consideration of human resources in the mixed-model sequencing problem with work overload

5. S. S. Kara and S. Onut, A two-stage stochastic and robust programming approach to strategic planning of a reverse supply

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analysis of finite-time stability in genetic regulatory networks with interval time-varying delays and leakage delay effects;AIMS Mathematics;2024

2. Mixed Production Line Optimization of Industrialized Building Based on Ant Colony Optimization Algorithm;Advances in Civil Engineering;2022-08-18

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