Multi-load AGVS deadlock prevention task scheduling method based on improved imperialist competition algorithm

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Udgivet i:Complex & Intelligent Systems vol. 11, no. 12 (Dec 2025), p. 471
Hovedforfatter: Xiao, Haining
Andre forfattere: Zhao, Bin, Zhang, Biao, Wang, Min
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Springer Nature B.V.
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022 |a 2199-4536 
022 |a 2198-6053 
024 7 |a 10.1007/s40747-025-02097-z  |2 doi 
035 |a 3264792340 
045 2 |b d20251201  |b d20251231 
100 1 |a Xiao, Haining  |u Yancheng Institute of Technology, College of Mechanical Engineering, Yancheng, China (GRID:grid.410613.1) (ISNI:0000 0004 1798 2282) 
245 1 |a Multi-load AGVS deadlock prevention task scheduling method based on improved imperialist competition algorithm 
260 |b Springer Nature B.V.  |c Dec 2025 
513 |a Journal Article 
520 3 |a Vehicle production involves a complex process and fast production pace, necessitating timely material delivery. The task scheduling problem of multi-load Automated Guided Vehicle System (AGVS) for auxiliary material distribution in automotive production workshops presents multiple optimization objectives and complex constraints. To enhance on-time delivery of auxiliary materials, this paper proposes a multi-load AGVS deadlock prevention task scheduling method based on improved Imperialist Competition Algorithm (ICA). First, a mathematical model for multi-load AGVS task scheduling is established, aiming to minimize task delivery distance and maximize the remaining time before the production line shuts down due to material shortages. By analyzing the conditions triggering deadlocks in multi-load AGVS, a deadlock prevention constraint based on the remaining trailer capacity of the buffer area is incorporated into the mathematical model. Second, an improved ICA (IICA) based deadlock prevention task scheduling method is designed. To enhance the initial national population quality of the IICA, a heuristic scheduling rule library is constructed to generate high-quality countries. An improved differential evolution algorithm is introduced during the assimilation process to improve convergence speed. Finally, a simulation platform for multi-load AGVS auxiliary material distribution is established. Experimental results indicate that the designed deadlock avoidance strategy effectively prevents deadlock occurrences while enhancing system productivity across all six algorithms. Compared to the other five algorithms, the proposed IICA achieves the highest unit hour production capacity, on-time task completion rate, and production line start-up rate, while maintaining the lowest average task execution time. 
653 |a Integer programming 
653 |a Task scheduling 
653 |a Mathematical models 
653 |a Workshops 
653 |a Delivery scheduling 
653 |a Automobiles 
653 |a Job shops 
653 |a Automation 
653 |a Automated guided vehicles 
653 |a Heuristic 
653 |a Performance evaluation 
653 |a Automobile production 
653 |a Energy consumption 
653 |a Evolutionary algorithms 
653 |a Mathematical programming 
653 |a Scheduling 
653 |a Evolutionary computation 
653 |a Imperialism 
653 |a Heuristic scheduling 
653 |a Assembly lines 
653 |a Production lines 
653 |a Genetic algorithms 
653 |a Design 
653 |a Linear programming 
653 |a Methods 
653 |a Literature reviews 
653 |a Constraints 
653 |a Optimization algorithms 
653 |a Materials handling 
700 1 |a Zhao, Bin  |u Yancheng Institute of Technology, College of Mechanical Engineering, Yancheng, China (GRID:grid.410613.1) (ISNI:0000 0004 1798 2282) 
700 1 |a Zhang, Biao  |u Yancheng Institute of Technology, College of Mechanical Engineering, Yancheng, China (GRID:grid.410613.1) (ISNI:0000 0004 1798 2282) 
700 1 |a Wang, Min  |u Yancheng Institute of Technology, College of Mechanical Engineering, Yancheng, China (GRID:grid.410613.1) (ISNI:0000 0004 1798 2282) 
773 0 |t Complex & Intelligent Systems  |g vol. 11, no. 12 (Dec 2025), p. 471 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3264792340/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3264792340/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3264792340/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch