Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow
Automatic guided vehicles (AGVs) are extensively employed in manufacturing workshops for their high degree of automation and flexibility. This paper investigates a limited AGV scheduling problem (LAGVSP) in matrix manufacturing workshops with undirected material flow, aiming to minimize both total t...
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Tsinghua University Press
2025-03-01
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| Series: | Complex System Modeling and Simulation |
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| Online Access: | https://www.sciopen.com/article/10.23919/CSMS.2024.0023 |
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| author | Xuewu Wang Jianing Zhang Yi Hua Rui Yu |
| author_facet | Xuewu Wang Jianing Zhang Yi Hua Rui Yu |
| author_sort | Xuewu Wang |
| collection | DOAJ |
| description | Automatic guided vehicles (AGVs) are extensively employed in manufacturing workshops for their high degree of automation and flexibility. This paper investigates a limited AGV scheduling problem (LAGVSP) in matrix manufacturing workshops with undirected material flow, aiming to minimize both total task delay time and total task completion time. To address this LAGVSP, a mixed-integer linear programming model is built, and a nondominated sorting genetic algorithm II based on dual population co-evolution (NSGA-IIDPC) is proposed. In NSGA-IIDPC, a single population is divided into a common population and an elite population, and they adopt different evolutionary strategies during the evolution process. The dual population co-evolution mechanism is designed to accelerate the convergence of the non-dominated solution set in the population to the Pareto front through information exchange and competition between the two populations. In addition, to enhance the quality of initial population, a minimum cost function strategy based on load balancing is adopted. Multiple local search operators based on ideal point are proposed to find a better local solution. To improve the global exploration ability of the algorithm, a dual population restart mechanism is adopted. Experimental tests and comparisons with other algorithms are conducted to demonstrate the effectiveness of NSGA-IIDPC in solving the LAGVSP. |
| format | Article |
| id | doaj-art-e4bb1b511ea045b6aae89a11eac16672 |
| institution | Kabale University |
| issn | 2096-9929 2097-3705 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Tsinghua University Press |
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| series | Complex System Modeling and Simulation |
| spelling | doaj-art-e4bb1b511ea045b6aae89a11eac166722025-08-20T03:40:17ZengTsinghua University PressComplex System Modeling and Simulation2096-99292097-37052025-03-0151688510.23919/CSMS.2024.0023Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material FlowXuewu Wang0Jianing Zhang1Yi Hua2Rui Yu3School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, ChinaInstitute for Sustainable Manufacturing, and also with the Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506, USAAutomatic guided vehicles (AGVs) are extensively employed in manufacturing workshops for their high degree of automation and flexibility. This paper investigates a limited AGV scheduling problem (LAGVSP) in matrix manufacturing workshops with undirected material flow, aiming to minimize both total task delay time and total task completion time. To address this LAGVSP, a mixed-integer linear programming model is built, and a nondominated sorting genetic algorithm II based on dual population co-evolution (NSGA-IIDPC) is proposed. In NSGA-IIDPC, a single population is divided into a common population and an elite population, and they adopt different evolutionary strategies during the evolution process. The dual population co-evolution mechanism is designed to accelerate the convergence of the non-dominated solution set in the population to the Pareto front through information exchange and competition between the two populations. In addition, to enhance the quality of initial population, a minimum cost function strategy based on load balancing is adopted. Multiple local search operators based on ideal point are proposed to find a better local solution. To improve the global exploration ability of the algorithm, a dual population restart mechanism is adopted. Experimental tests and comparisons with other algorithms are conducted to demonstrate the effectiveness of NSGA-IIDPC in solving the LAGVSP.https://www.sciopen.com/article/10.23919/CSMS.2024.0023limited automatic guided vehicle (agv) scheduling problemnondominated sorting genetic algorithm ii (nsga-ii)dual population co-evolutionmatrix manufacturing workshop |
| spellingShingle | Xuewu Wang Jianing Zhang Yi Hua Rui Yu Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow Complex System Modeling and Simulation limited automatic guided vehicle (agv) scheduling problem nondominated sorting genetic algorithm ii (nsga-ii) dual population co-evolution matrix manufacturing workshop |
| title | Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow |
| title_full | Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow |
| title_fullStr | Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow |
| title_full_unstemmed | Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow |
| title_short | Effective NSGA-II Algorithm for a Limited AGV Scheduling Problem in Matrix Manufacturing Workshops with Undirected Material Flow |
| title_sort | effective nsga ii algorithm for a limited agv scheduling problem in matrix manufacturing workshops with undirected material flow |
| topic | limited automatic guided vehicle (agv) scheduling problem nondominated sorting genetic algorithm ii (nsga-ii) dual population co-evolution matrix manufacturing workshop |
| url | https://www.sciopen.com/article/10.23919/CSMS.2024.0023 |
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