TY - GEN
T1 - Scheduling method of maintenance support resource with task timing constraint
AU - Guan, Chongchong
AU - Lu, Hui
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Maintenance support resource scheduling (MSRS) problem has attracted increasing attention in modern battle. It aims to allocate resources from multi-supply points to multi-tasks with the shortest time. However, there exists various constraints which are difficult to satisfy at the same time, such as limited resource reserves, different resource requirements, complex route conditions and strict task timing. As a result, we first obtain the shortest routes and task sequence with route planning and topological sorting algorithms separately. Then, with these information, an integrated meta-heuristic algorithm (IMHA) is designed to solve all the constraints. Furthermore, two improved algorithms, CMHA and GMHA are generated with classical and greedy scheduling strategies respectively. Experiment results show the feasibility of IMHA in solving the MSRS problem with timing constraint. Besides, compared with the IMHA, the GMHA and CMHA can generate scheduling schemes with lower cost and time in the whole 24 instances. In addition, as the increase of proportion of timing tasks, the advantages of GMHA in cost and time are more evident.
AB - Maintenance support resource scheduling (MSRS) problem has attracted increasing attention in modern battle. It aims to allocate resources from multi-supply points to multi-tasks with the shortest time. However, there exists various constraints which are difficult to satisfy at the same time, such as limited resource reserves, different resource requirements, complex route conditions and strict task timing. As a result, we first obtain the shortest routes and task sequence with route planning and topological sorting algorithms separately. Then, with these information, an integrated meta-heuristic algorithm (IMHA) is designed to solve all the constraints. Furthermore, two improved algorithms, CMHA and GMHA are generated with classical and greedy scheduling strategies respectively. Experiment results show the feasibility of IMHA in solving the MSRS problem with timing constraint. Besides, compared with the IMHA, the GMHA and CMHA can generate scheduling schemes with lower cost and time in the whole 24 instances. In addition, as the increase of proportion of timing tasks, the advantages of GMHA in cost and time are more evident.
KW - Integrate meta-heuristic algorithm
KW - Maintenance support resource scheduling problem
KW - classical
KW - greedy
KW - routes planning
KW - timing constraint
UR - https://www.scopus.com/pages/publications/85080921005
U2 - 10.1109/SSCI44817.2019.9003132
DO - 10.1109/SSCI44817.2019.9003132
M3 - 会议稿件
AN - SCOPUS:85080921005
T3 - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
SP - 2698
EP - 2705
BT - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
Y2 - 6 December 2019 through 9 December 2019
ER -