Intelligent Scheduling of a Pulsating Assembly Flow Shop Considering a Multifunctional Automated Guided Vehicle

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Publicat a:Applied Sciences vol. 15, no. 5 (2025), p. 2593
Autor principal: Song, Hailong
Altres autors: Yang, Shengluo, Yin, Shuoxin, Wang, Junyi, Xu, Zhigang
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MDPI AG
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022 |a 2076-3417 
024 7 |a 10.3390/app15052593  |2 doi 
035 |a 3176306853 
045 2 |b d20250101  |b d20251231 
084 |a 231338  |2 nlm 
100 1 |a Song, Hailong  |u Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; <email>songhailong@sia.cn</email> (H.S.); <email>jywang@sia.cn</email> (J.W.); <email>zgxu@sia.cn</email> (Z.X.); University of Chinese Academy of Sciences, Beijing 100049, China 
245 1 |a Intelligent Scheduling of a Pulsating Assembly Flow Shop Considering a Multifunctional Automated Guided Vehicle 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a The pulsating assembly line is widely used in modern manufacturing, particularly in high-precision industries such as aerospace, where it greatly enhances production efficiency. To achieve overall optimization, both product scheduling and Automated Guided Vehicle (AGV) scheduling must be simultaneously optimized. However, existing research predominantly focuses on product scheduling, with limited attention given to AGV scheduling. This paper proposes an optimized solution for the pulsating assembly line scheduling problem, incorporating multifunctional AGV scheduling. A mathematical model is developed and three AGV selection strategies and three AGV standby strategies are designed to optimize AGV scheduling and control. To improve scheduling efficiency, nine heuristic strategies are introduced, along with the Variable Neighborhood Descent (VND) algorithm as a metaheuristic method for product scheduling. The VND algorithm refines the solution through multiple neighborhood searches, enhancing both the precision and efficiency of product scheduling. Our experimental results demonstrate that the proposed strategies significantly improve the production efficiency of pulsating assembly workshops, reduce AGV scheduling costs, and optimize overall production workflows. This study offers novel methods for intelligent scheduling in pulsating assembly workshops, contributing to the advancement of manufacturing toward “multiple varieties, small batches, and customization”. 
653 |a Scheduling 
653 |a Design 
653 |a Job shops 
653 |a Linear programming 
653 |a Production planning 
653 |a Deep learning 
653 |a Assembly lines 
653 |a Algorithms 
653 |a Automation 
653 |a Manufacturing 
653 |a Mathematical models 
653 |a Optimization 
653 |a Efficiency 
700 1 |a Yang, Shengluo  |u School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; <email>yinshuoxin1223@163.com</email> 
700 1 |a Yin, Shuoxin  |u School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; <email>yinshuoxin1223@163.com</email> 
700 1 |a Wang, Junyi  |u Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; <email>songhailong@sia.cn</email> (H.S.); <email>jywang@sia.cn</email> (J.W.); <email>zgxu@sia.cn</email> (Z.X.) 
700 1 |a Xu, Zhigang  |u Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; <email>songhailong@sia.cn</email> (H.S.); <email>jywang@sia.cn</email> (J.W.); <email>zgxu@sia.cn</email> (Z.X.) 
773 0 |t Applied Sciences  |g vol. 15, no. 5 (2025), p. 2593 
786 0 |d ProQuest  |t Publicly Available Content Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3176306853/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3176306853/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3176306853/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch