TY - GEN
T1 - Integrated Scheduling of Flexible Job Shop and Energy-Efficient Automated Guided Vehicles
AU - Zhang, Lixiang
AU - Yan, Yan
AU - Hu, Yaoguang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Intelligent machines and automated guide vehicles (AGVs) have been widely applied to improve the flexibility of manufacturing systems. However, the energy consumption and battery management of AGVs are not well considered. Therefore, this paper proposes an integrated scheduling method for solving flexible job shop scheduling problems (FJSP) with energy-efficient AGVs to minimize the makespan and energy consumption. Besides, a novel hybrid genetic algorithm (HGA) with a local neighbor search (LNS) is developed to optimize the objective. Results indicate that the proposed HGA obtains a shorter makespan and lower energy consumption than the genetic algorithm. Finally, we verify the model and present the integrated scheduling solutions of FJSP with energy-efficient AGVs. It indicates the proposed method has significant potential for intelligent manufacturing systems.
AB - Intelligent machines and automated guide vehicles (AGVs) have been widely applied to improve the flexibility of manufacturing systems. However, the energy consumption and battery management of AGVs are not well considered. Therefore, this paper proposes an integrated scheduling method for solving flexible job shop scheduling problems (FJSP) with energy-efficient AGVs to minimize the makespan and energy consumption. Besides, a novel hybrid genetic algorithm (HGA) with a local neighbor search (LNS) is developed to optimize the objective. Results indicate that the proposed HGA obtains a shorter makespan and lower energy consumption than the genetic algorithm. Finally, we verify the model and present the integrated scheduling solutions of FJSP with energy-efficient AGVs. It indicates the proposed method has significant potential for intelligent manufacturing systems.
UR - http://www.scopus.com/inward/record.url?scp=85171557468&partnerID=8YFLogxK
U2 - 10.1109/ICARM58088.2023.10218812
DO - 10.1109/ICARM58088.2023.10218812
M3 - Conference contribution
AN - SCOPUS:85171557468
T3 - 2023 8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023
SP - 493
EP - 498
BT - 2023 8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023
Y2 - 8 July 2023 through 10 July 2023
ER -
