TY - GEN
T1 - A Simulation Hyper-Heuristic Method for Multi-Floor AGV Delivery Services in Hospitals
AU - Yuan, Haocheng
AU - Chen, Xinan
AU - Zhu, Junsong
AU - Bai, Ruibin
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Automated Guided Vehicles (AGVs) enhance transportation efficiency in different domains such as warehouses, factories, and container ports. Much research has been done into optimal scheduling and routing of multiple AGVs to improve the overall efficiency of the systems. However, more research efforts are required when addressing more complex real-life systems where the mobility of AGVs is highly constrained due to special geometric shapes and dimensions. Focusing on a real-world hospital AGV routing problem, this paper tackles the additional complexity arising from space capacity constraints long narrow corridors and lifts for cross-floor deliveries. A simulation optimisation approach is introduced to accurately model complex interactions of AGVs under conditions like floor switching, charging, and passing narrow corridors. To tackle the underlining vehicle routing problems with pickup and delivery (VRPPD) which is NP-Hard, this paper presents a simulation-based hyper-heuristic optimization approach to minimize the makespan of all tasks. A surrogate model is integrated to expedite the search process, and several experiments are conducted to properly evaluate the performance of our method. Based on the results, our method exhibits great potential in improving efficiency while maintaining the excellent practicality of AGV routing for complex environments like hospitals.
AB - Automated Guided Vehicles (AGVs) enhance transportation efficiency in different domains such as warehouses, factories, and container ports. Much research has been done into optimal scheduling and routing of multiple AGVs to improve the overall efficiency of the systems. However, more research efforts are required when addressing more complex real-life systems where the mobility of AGVs is highly constrained due to special geometric shapes and dimensions. Focusing on a real-world hospital AGV routing problem, this paper tackles the additional complexity arising from space capacity constraints long narrow corridors and lifts for cross-floor deliveries. A simulation optimisation approach is introduced to accurately model complex interactions of AGVs under conditions like floor switching, charging, and passing narrow corridors. To tackle the underlining vehicle routing problems with pickup and delivery (VRPPD) which is NP-Hard, this paper presents a simulation-based hyper-heuristic optimization approach to minimize the makespan of all tasks. A surrogate model is integrated to expedite the search process, and several experiments are conducted to properly evaluate the performance of our method. Based on the results, our method exhibits great potential in improving efficiency while maintaining the excellent practicality of AGV routing for complex environments like hospitals.
KW - AGV congestion
KW - hyper-heuristic
KW - multi-floor AGV routing
KW - pickup and delivery problem
KW - simulation-based optimization
UR - http://www.scopus.com/inward/record.url?scp=85182917956&partnerID=8YFLogxK
U2 - 10.1109/SSCI52147.2023.10371983
DO - 10.1109/SSCI52147.2023.10371983
M3 - Conference Proceeding
AN - SCOPUS:85182917956
T3 - 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
SP - 1221
EP - 1226
BT - 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
Y2 - 5 December 2023 through 8 December 2023
ER -