Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints

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Publicat a:Agriculture vol. 15, no. 4 (2025), p. 442
Autor principal: Zhangliang Wei
Altres autors: Yu, Zipeng, Niu, Renzhong, Zhao, Qilong, Li, Zhigang
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MDPI AG
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024 7 |a 10.3390/agriculture15040442  |2 doi 
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045 2 |b d20250101  |b d20251231 
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100 1 |a Zhangliang Wei  |u College of Information Science and Technology, Shihezi University, Shihezi 832000, China; <email>wzl_shzu@shzu.edu.cn</email> (Z.W.); <email>yuzipeng@stu.shzu.edu.cn</email> (Z.Y.); <email>20242108038@stu.shzu.edu.cn</email> (Q.Z.); College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China; <email>nrz1994@stu.shzu.edu.cn</email> 
245 1 |a Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterprises. The flexible job shop scheduling problem (FJSP) in the context of agricultural machinery and equipment manufacturing is addressed, which involves multiple resources including machines, workers, and automated guided vehicles (AGVs). The aim is to optimize two objectives: makespan and the maximum continuous working hours of all workers. To tackle this complex problem, a Multi-Objective Discrete Grey Wolf Optimization (MODGWO) algorithm is proposed. The MODGWO algorithm integrates a hybrid initialization strategy and a multi-neighborhood local search to effectively balance the exploration and exploitation capabilities. An encoding/decoding method and a method for initializing a mixed population are introduced, which includes an operation sequence vector, machine selection vector, worker selection vector, and AGV selection vector. The solution-updating mechanism is also designed to be discrete. The performance of the MODGWO algorithm is evaluated through comprehensive experiments using an extended version of the classic Brandimarte test case by randomly adding worker and AGV information. The experimental results demonstrate that MODGWO achieves better performance in identifying high-quality solutions compared to other competitive algorithms, especially for medium- and large-scale cases. The proposed algorithm contributes to the research on flexible job shop scheduling under multi-resource constraints, providing a novel solution approach that comprehensively considers both workers and AGVs. The research findings have practical implications for improving production efficiency and balancing multiple objectives in agricultural machinery and equipment manufacturing enterprises. 
653 |a Integer programming 
653 |a Mathematical models 
653 |a Algorithms 
653 |a Workers 
653 |a Workshops 
653 |a Agricultural technology 
653 |a Optimization 
653 |a Productivity 
653 |a Job shops 
653 |a Agriculture 
653 |a Multiple objective analysis 
653 |a Manufacturing 
653 |a Automated guided vehicles 
653 |a Tax regulations 
653 |a Energy consumption 
653 |a Climate change 
653 |a Farmworkers 
653 |a Efficiency 
653 |a Scheduling 
653 |a Agricultural equipment 
653 |a Genetic algorithms 
653 |a Manufacturing industry 
653 |a Flexibility 
653 |a Resource scheduling 
653 |a Encoding-Decoding 
653 |a Methods 
653 |a Working hours 
653 |a Constraints 
653 |a Farm machinery 
653 |a Production methods 
653 |a Job shop scheduling 
653 |a Economic 
700 1 |a Yu, Zipeng  |u College of Information Science and Technology, Shihezi University, Shihezi 832000, China; <email>wzl_shzu@shzu.edu.cn</email> (Z.W.); <email>yuzipeng@stu.shzu.edu.cn</email> (Z.Y.); <email>20242108038@stu.shzu.edu.cn</email> (Q.Z.) 
700 1 |a Niu, Renzhong  |u College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China; <email>nrz1994@stu.shzu.edu.cn</email> 
700 1 |a Zhao, Qilong  |u College of Information Science and Technology, Shihezi University, Shihezi 832000, China; <email>wzl_shzu@shzu.edu.cn</email> (Z.W.); <email>yuzipeng@stu.shzu.edu.cn</email> (Z.Y.); <email>20242108038@stu.shzu.edu.cn</email> (Q.Z.) 
700 1 |a Li, Zhigang  |u College of Information Science and Technology, Shihezi University, Shihezi 832000, China; <email>wzl_shzu@shzu.edu.cn</email> (Z.W.); <email>yuzipeng@stu.shzu.edu.cn</email> (Z.Y.); <email>20242108038@stu.shzu.edu.cn</email> (Q.Z.) 
773 0 |t Agriculture  |g vol. 15, no. 4 (2025), p. 442 
786 0 |d ProQuest  |t Agriculture Science Database 
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