How to cite this paper
Li, Y., Zou, J., Jia, Y., Meng, L & Zou, W. (2023). An improved genetic algorithm for multi-AGV dispatching problem with unloading setup time in a matrix manufacturing workshop.International Journal of Industrial Engineering Computations , 14(4), 767-784.
Refrences
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Chen, C., Tiong, L. K., & Chen, I.-M. (2019). Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system. International Journal of Production Research, 57(10), 3003–3019.
Chen, X., Wu, W., & Hu, R. (2022). A Novel Multi-AGV Coordination Strategy Based on the Combination of Nodes and Grids. IEEE Robotics and Automation Letters, 7(3), 6218-6225.
Eda, S., Nishi, T., Mariyama, T., Kataoka, S., Shoda, K., & Matsumura, K. (2012). Petri net decomposition approach for bi-objective routing for AGV systems minimizing total traveling time and equalizing delivery time. Journal of Advanced Mechanical Design Systems and Manufacturing, 6(5), 672–686.
Ha, W. Y., Cui, L., & Jiang, Z.-P. (2021). A warehouse scheduling using genetic algorithm and collision index. 2021 20th International Conference on Advanced Robotics (ICAR), 318–323. https://doi.org /10.1109/ICAR53236.2021.9659439
Hao, J., Wang, C., Yang, M., & Wang, B. (2020). Hybrid genetic algorithm based dispatch and conflict-free routing method of agv systems in unmanned underground parking lots. In 2020 IEEE international conference on real-time computing and robotics (RCAR), 475-480 https://doi.org/10.1109/RCAR49640.2020.9303275.
Hu, Y. J., Dong, L. C., & Xu, L. (2020). Multi-AGV dispatching and routing problem based on a three-stage decomposition method. Mathematical Biosciences and Engineering, 17(5), 5150–5172.
Huang, S. J., Lee, T. S., Li, W. H., & Chen, R. Y. (2018). Modular on-road AGV wireless charging systems via interoperable power adjustment. IEEE Transactions on Industrial Electronics, 66(8), 5918-5928.
Jahanzaib, M., Masood, S. A., Nadeem, S., Akhtar, K., & Shahbaz, M. (2013). Application of genetic algorithm (ga) approach in the formation of manufacturing cells for group technology. Life Science Journal, 9(4), 799-809.
Jin, J., & Zhang, X. H. (2016). Multi AGV scheduling problem in automated container terminal. Journal of Marine Science and Technology-Taiwan, 24(1), 32–38.
Li, G., Li, X., Gao, L., & Zeng, B. (2019). Tasks assigning and sequencing of multiple AGVs based on an improved harmony search algorithm. Journal of Ambient Intelligence and Humanized Computing, 10(11), 4533–4546.
Li, H., Gao, K., Duan, P. Y., Li, J. Q., & Zhang, L. (2022). An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems. IEEE Transactions on Systems, Man, and Cybernetics: Systems. https://doi.org/10.1109/TSMC.2022.3219380
Li, J., Cheng, W., Lai, K. K., & Ram, B. (2022). Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging. Mathematics, 10(19), 3417.
Li, Z. K., Sang, H. Y., Li, J. Q., Han, Y. Y., Gao, K. Z., Zheng, Z. X., & Liu, L. L. (2023). Invasive Weed Optimization for multi-AGVs dispatching problem in a matrix manufacturing workshop. Swarm and Evolutionary Computation, 101227.
Lu, S., Xu, C., Zhong, R. Y., & Wang, L. (2017). A RFID-enabled positioning system in automated guided vehicle for smart factories. Journal of Manufacturing Systems, 44, 179-190.
Liu, L., Qu, T., Thurer, M., Ma, L., Zhang, Z., & Yuan, M. (2022). A new knowledge-guided multi-objective optimisation for the multi-AGV dispatching problem in dynamic production environments. International Journal of Production Research. https://doi.org/10.1080/00207543.2022.2122619
Meng, L., Gao, K., Ren, Y., Zhang, B., Sang, H., & Chaoyong, Z. (2022). Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 71, 101058.
Meng, L., Cheng, W., Zhang, B., Zou, W., Fang, W., & Duan, P. (2023). An Improved Genetic Algorithm for Solving the Multi-AGV Flexible Job Shop Scheduling Problem. Sensors, 23(8), 3815.
Meng, L., Zhang, C., Ren, Y., Zhang, B., & Lv, C. (2020). Mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem. Computers & Industrial Engineering, 142, 106347.
Micieta, B., Edl, M., Krajcovic, M., Dulina, L., Bubenik, P., Durica, L., & Binasova, V. (2018). Delegate MASs for coordination and control of one-directional AGV systems: a proof-of-concept. The International Journal of Advanced Manufacturing Technology, 94, 415-431.
Ng, P. P. W., Yucel, G., & Duffy, V. G. (2009). Modelling the effect of AGV operating conditions on operator perception of acceptability and hazard. International Journal of Computer Integrated Manufacturing, 22(12), 1154–1162.
Nishida, K., & Nishi, T. (2022). Dynamic Optimization of Conflict-Free Routing of Automated Guided Vehicles for Just-in-Time Delivery. IEEE Transactions on Automation Science and Engineering. https://doi.org/10.1109/TASE.2022.3194082
Niu, H. Y., Wu, W. M., Xing, Z. C., Wang, X. K., & Zhang, T. (2023). A novel multi-tasks chain scheduling algorithm based on capacity prediction to solve AGV dispatching problem in an intelligent manufacturing system. Journal of Manufacturing Systems, 68, 130–144.
Ren, N., Zhao, Y., & Zhang, J. (2012). Scheduling research of AGV with double buffers based genetic algorithm in flexible manufacturing system. Applied Mechanics and Materials, 121, 1630-1635.
Routray, M., & Ray, N. K. (2020). Remote homology detection using GA and NSGA-II on physicochemical properties. International Journal of Computer Applications in Technology, 64(4), 393-402.
Singh, N., Dang, Q. V, Akcay, A., Adan, I., & Martagan, T. (2022). A matheuristic for AGV scheduling with battery constraints. European Journal of Operational Research, 298(3), 855–873.
Singh, V., & Choudhary, S. (2009). Genetic algorithm for traveling salesman problem: using modified partially-mapped crossover operator. 2009 International Conference on Multimedia, Signal Processing and Communication Technologies, 20–23. https://doi.org/10.1109/MSPCT.2009.5164164
Song, J. (2021). Automatic guided vehicle global path planning considering multi-objective optimization and speed control. Sensors and Materials, 33(6), 1999–2011.
Sun, P. Z., You, J., Qiu, S., Wu, E. Q., Xiong, P., Song, A., Zhang, H., & Lu, T. (2022). AGV-Based Vehicle Transportation in Automated Container Terminals: A Survey. IEEE Transactions on Intelligent Transportation Systems. https:// doi.org/10.1109/TITS.2022.3215776.
Wang, C., Wang, L., Qin, J., Wu, Z., Duan, L., Li, Z., Cao, M., Ou, X., Su, X., Li, W., Lu, Z., Li, M., Wang, Y., Long, J., Huang, M., Li, Y., & Wang, Q. (2015). Path planning of automated guided vehicles based on improved a-star algorithm. 2015 IEEE International Conference on Information and Automation, 2071–2076. https:// doi.org/10.1109/ICInfA.2015.7279630.
Wang, Z., & Wu, Y. (2023). An Ant Colony Optimization-Simulated Annealing Algorithm for Solving a Multiload AGVs Workshop Scheduling Problem with Limited Buffer Capacity. Processes, 11(3), 861.
Wang, Z., & Zeng, Q. (2022). A branch-and-bound approach for AGV dispatching and routing problems in automated container terminals. Computers & Industrial Engineering, 166, 107968.
Wei, Q., Yan, Y., Zhang, J., Xiao, J., & Wang, C. (2022). A self-attention-based deep reinforcement learning approach for AGV dispatching systems. IEEE Transactions on Neural Networks and Learning Systems. https:// doi.org/10.1109/TNNLS.2022.3222206.
Wu, S., Xiang, W., Li, W., Chen, L., & Wu, C. (2023). Dynamic Scheduling and Optimization of AGV in Factory Logistics Systems Based on Digital Twin. Applied Sciences, 13(3), 1762.
Xu, L., Wang, Y., Liu, L., & Wang, J. (2016). Exact and Heuristic Algorithms for Routing AGV on Path with Precedence Constraints. Mathematical Problems in Engineering, 8, 1-8.
Yao, F., Alkan, B., Ahmad, B., & Harrison, R. (2020). Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation. Sensors, 20(21), 6333.
Yuan, M. H., Li, Y. D., Pei, F. Q., & Gu, W. B. (2021). Dual-resource integrated scheduling method of AGV and machine in intelligent manufacturing job shop. Journal of Central South University, 28(8), 2423-2435.
Yuan, Z., Yang, Z., Lv, L., & Shi, Y. (2020). A bi-level path planning algorithm for multi-AGV routing problem. Electronics, 9(9), 1351.
Zhang, X. J., Sang, H. Y., Li, J. Q., Han, Y. Y., & Duan, P. (2022). An effective multi-AGVs dispatching method applied to matrix manufacturing workshop. Computers & Industrial Engineering, 163, 107791.
Zou, W. Q., Pan, Q. K., Meng, T., Gao, L., & Wang, Y. L. (2020). An effective discrete artificial bee colony algorithm for multi-AGVs dispatching problem in a matrix manufacturing workshop. Expert Systems with Applications, 161, 113675.
Zou, W. Q., Pan, Q. K., & Wang, L. (2021). An effective multi-objective evolutionary algorithm for solving the AGV scheduling problem with pickup and delivery. Knowledge-Based Systems, 218, 106881.
Zou, W. Q., Pan, Q. K., & Tasgetiren, M. F. (2021). An effective iterated greedy algorithm for solving a multi-compartment AGV scheduling problem in a matrix manufacturing workshop. Applied Soft Computing, 99, 106945.
Zou, W. Q., Pan, Q. K., Wang, L., Miao, Z. H., & Peng, C. (2022). Efficient multiobjective optimization for an AGV energy-efficient scheduling problem with release time. Knowledge-Based Systems, 242, 108334.
Zou, W. Q., Pan, Q. K., Meng, L. L., Sang, H. Y., Han, Y. Y., & Li, J. Q. (2023). An effective self-adaptive iterated greedy algorithm for a multi-AGVs scheduling problem with charging and maintenance. Expert Systems with Applications, 119512.
Chen, C., Tiong, L. K., & Chen, I.-M. (2019). Using a genetic algorithm to schedule the space-constrained AGV-based prefabricated bathroom units manufacturing system. International Journal of Production Research, 57(10), 3003–3019.
Chen, X., Wu, W., & Hu, R. (2022). A Novel Multi-AGV Coordination Strategy Based on the Combination of Nodes and Grids. IEEE Robotics and Automation Letters, 7(3), 6218-6225.
Eda, S., Nishi, T., Mariyama, T., Kataoka, S., Shoda, K., & Matsumura, K. (2012). Petri net decomposition approach for bi-objective routing for AGV systems minimizing total traveling time and equalizing delivery time. Journal of Advanced Mechanical Design Systems and Manufacturing, 6(5), 672–686.
Ha, W. Y., Cui, L., & Jiang, Z.-P. (2021). A warehouse scheduling using genetic algorithm and collision index. 2021 20th International Conference on Advanced Robotics (ICAR), 318–323. https://doi.org /10.1109/ICAR53236.2021.9659439
Hao, J., Wang, C., Yang, M., & Wang, B. (2020). Hybrid genetic algorithm based dispatch and conflict-free routing method of agv systems in unmanned underground parking lots. In 2020 IEEE international conference on real-time computing and robotics (RCAR), 475-480 https://doi.org/10.1109/RCAR49640.2020.9303275.
Hu, Y. J., Dong, L. C., & Xu, L. (2020). Multi-AGV dispatching and routing problem based on a three-stage decomposition method. Mathematical Biosciences and Engineering, 17(5), 5150–5172.
Huang, S. J., Lee, T. S., Li, W. H., & Chen, R. Y. (2018). Modular on-road AGV wireless charging systems via interoperable power adjustment. IEEE Transactions on Industrial Electronics, 66(8), 5918-5928.
Jahanzaib, M., Masood, S. A., Nadeem, S., Akhtar, K., & Shahbaz, M. (2013). Application of genetic algorithm (ga) approach in the formation of manufacturing cells for group technology. Life Science Journal, 9(4), 799-809.
Jin, J., & Zhang, X. H. (2016). Multi AGV scheduling problem in automated container terminal. Journal of Marine Science and Technology-Taiwan, 24(1), 32–38.
Li, G., Li, X., Gao, L., & Zeng, B. (2019). Tasks assigning and sequencing of multiple AGVs based on an improved harmony search algorithm. Journal of Ambient Intelligence and Humanized Computing, 10(11), 4533–4546.
Li, H., Gao, K., Duan, P. Y., Li, J. Q., & Zhang, L. (2022). An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems. IEEE Transactions on Systems, Man, and Cybernetics: Systems. https://doi.org/10.1109/TSMC.2022.3219380
Li, J., Cheng, W., Lai, K. K., & Ram, B. (2022). Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging. Mathematics, 10(19), 3417.
Li, Z. K., Sang, H. Y., Li, J. Q., Han, Y. Y., Gao, K. Z., Zheng, Z. X., & Liu, L. L. (2023). Invasive Weed Optimization for multi-AGVs dispatching problem in a matrix manufacturing workshop. Swarm and Evolutionary Computation, 101227.
Lu, S., Xu, C., Zhong, R. Y., & Wang, L. (2017). A RFID-enabled positioning system in automated guided vehicle for smart factories. Journal of Manufacturing Systems, 44, 179-190.
Liu, L., Qu, T., Thurer, M., Ma, L., Zhang, Z., & Yuan, M. (2022). A new knowledge-guided multi-objective optimisation for the multi-AGV dispatching problem in dynamic production environments. International Journal of Production Research. https://doi.org/10.1080/00207543.2022.2122619
Meng, L., Gao, K., Ren, Y., Zhang, B., Sang, H., & Chaoyong, Z. (2022). Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times. Swarm and Evolutionary Computation, 71, 101058.
Meng, L., Cheng, W., Zhang, B., Zou, W., Fang, W., & Duan, P. (2023). An Improved Genetic Algorithm for Solving the Multi-AGV Flexible Job Shop Scheduling Problem. Sensors, 23(8), 3815.
Meng, L., Zhang, C., Ren, Y., Zhang, B., & Lv, C. (2020). Mixed-integer linear programming and constraint programming formulations for solving distributed flexible job shop scheduling problem. Computers & Industrial Engineering, 142, 106347.
Micieta, B., Edl, M., Krajcovic, M., Dulina, L., Bubenik, P., Durica, L., & Binasova, V. (2018). Delegate MASs for coordination and control of one-directional AGV systems: a proof-of-concept. The International Journal of Advanced Manufacturing Technology, 94, 415-431.
Ng, P. P. W., Yucel, G., & Duffy, V. G. (2009). Modelling the effect of AGV operating conditions on operator perception of acceptability and hazard. International Journal of Computer Integrated Manufacturing, 22(12), 1154–1162.
Nishida, K., & Nishi, T. (2022). Dynamic Optimization of Conflict-Free Routing of Automated Guided Vehicles for Just-in-Time Delivery. IEEE Transactions on Automation Science and Engineering. https://doi.org/10.1109/TASE.2022.3194082
Niu, H. Y., Wu, W. M., Xing, Z. C., Wang, X. K., & Zhang, T. (2023). A novel multi-tasks chain scheduling algorithm based on capacity prediction to solve AGV dispatching problem in an intelligent manufacturing system. Journal of Manufacturing Systems, 68, 130–144.
Ren, N., Zhao, Y., & Zhang, J. (2012). Scheduling research of AGV with double buffers based genetic algorithm in flexible manufacturing system. Applied Mechanics and Materials, 121, 1630-1635.
Routray, M., & Ray, N. K. (2020). Remote homology detection using GA and NSGA-II on physicochemical properties. International Journal of Computer Applications in Technology, 64(4), 393-402.
Singh, N., Dang, Q. V, Akcay, A., Adan, I., & Martagan, T. (2022). A matheuristic for AGV scheduling with battery constraints. European Journal of Operational Research, 298(3), 855–873.
Singh, V., & Choudhary, S. (2009). Genetic algorithm for traveling salesman problem: using modified partially-mapped crossover operator. 2009 International Conference on Multimedia, Signal Processing and Communication Technologies, 20–23. https://doi.org/10.1109/MSPCT.2009.5164164
Song, J. (2021). Automatic guided vehicle global path planning considering multi-objective optimization and speed control. Sensors and Materials, 33(6), 1999–2011.
Sun, P. Z., You, J., Qiu, S., Wu, E. Q., Xiong, P., Song, A., Zhang, H., & Lu, T. (2022). AGV-Based Vehicle Transportation in Automated Container Terminals: A Survey. IEEE Transactions on Intelligent Transportation Systems. https:// doi.org/10.1109/TITS.2022.3215776.
Wang, C., Wang, L., Qin, J., Wu, Z., Duan, L., Li, Z., Cao, M., Ou, X., Su, X., Li, W., Lu, Z., Li, M., Wang, Y., Long, J., Huang, M., Li, Y., & Wang, Q. (2015). Path planning of automated guided vehicles based on improved a-star algorithm. 2015 IEEE International Conference on Information and Automation, 2071–2076. https:// doi.org/10.1109/ICInfA.2015.7279630.
Wang, Z., & Wu, Y. (2023). An Ant Colony Optimization-Simulated Annealing Algorithm for Solving a Multiload AGVs Workshop Scheduling Problem with Limited Buffer Capacity. Processes, 11(3), 861.
Wang, Z., & Zeng, Q. (2022). A branch-and-bound approach for AGV dispatching and routing problems in automated container terminals. Computers & Industrial Engineering, 166, 107968.
Wei, Q., Yan, Y., Zhang, J., Xiao, J., & Wang, C. (2022). A self-attention-based deep reinforcement learning approach for AGV dispatching systems. IEEE Transactions on Neural Networks and Learning Systems. https:// doi.org/10.1109/TNNLS.2022.3222206.
Wu, S., Xiang, W., Li, W., Chen, L., & Wu, C. (2023). Dynamic Scheduling and Optimization of AGV in Factory Logistics Systems Based on Digital Twin. Applied Sciences, 13(3), 1762.
Xu, L., Wang, Y., Liu, L., & Wang, J. (2016). Exact and Heuristic Algorithms for Routing AGV on Path with Precedence Constraints. Mathematical Problems in Engineering, 8, 1-8.
Yao, F., Alkan, B., Ahmad, B., & Harrison, R. (2020). Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation. Sensors, 20(21), 6333.
Yuan, M. H., Li, Y. D., Pei, F. Q., & Gu, W. B. (2021). Dual-resource integrated scheduling method of AGV and machine in intelligent manufacturing job shop. Journal of Central South University, 28(8), 2423-2435.
Yuan, Z., Yang, Z., Lv, L., & Shi, Y. (2020). A bi-level path planning algorithm for multi-AGV routing problem. Electronics, 9(9), 1351.
Zhang, X. J., Sang, H. Y., Li, J. Q., Han, Y. Y., & Duan, P. (2022). An effective multi-AGVs dispatching method applied to matrix manufacturing workshop. Computers & Industrial Engineering, 163, 107791.
Zou, W. Q., Pan, Q. K., Meng, T., Gao, L., & Wang, Y. L. (2020). An effective discrete artificial bee colony algorithm for multi-AGVs dispatching problem in a matrix manufacturing workshop. Expert Systems with Applications, 161, 113675.
Zou, W. Q., Pan, Q. K., & Wang, L. (2021). An effective multi-objective evolutionary algorithm for solving the AGV scheduling problem with pickup and delivery. Knowledge-Based Systems, 218, 106881.
Zou, W. Q., Pan, Q. K., & Tasgetiren, M. F. (2021). An effective iterated greedy algorithm for solving a multi-compartment AGV scheduling problem in a matrix manufacturing workshop. Applied Soft Computing, 99, 106945.
Zou, W. Q., Pan, Q. K., Wang, L., Miao, Z. H., & Peng, C. (2022). Efficient multiobjective optimization for an AGV energy-efficient scheduling problem with release time. Knowledge-Based Systems, 242, 108334.
Zou, W. Q., Pan, Q. K., Meng, L. L., Sang, H. Y., Han, Y. Y., & Li, J. Q. (2023). An effective self-adaptive iterated greedy algorithm for a multi-AGVs scheduling problem with charging and maintenance. Expert Systems with Applications, 119512.