@inproceedings{4c79f3a4a9644f29bb1c5352d57fdd28,
title = "Cooperative multiple task assignment using cluster method and bidirectional particle swarm optimization",
abstract = "The cooperative multiple task assignment problem with heterogeneous UAVs demands different UAVS to executed multiple tasks on each target obeying peculiar order of task type. This is a typical NP-hard problem. However, the deadlock situation makes solving process in trouble without appropriate task execution order. In this paper, the precedent targets order is given by cluster method to avoiding the deadlock situation and the bidirectional particle swarm optimization (BPSO) is applied for assigning heterogeneous UAVs to accomplish each task of each target. Then simulation experiments are given to demonstrate the feasibility of BPSO. What's more, the robust performance and optimality are better than random search algorithm by the result of Monte Carlo simulations.",
keywords = "PSO, cluster mothed, cooperative task assignment, deadlock\_free, heterogeneous UAVs",
author = "Weiyong Tian and Li Liu and Qiusheng Wang and Han Mu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021 ; Conference date: 18-06-2021 Through 20-06-2021",
year = "2021",
month = jun,
day = "18",
doi = "10.1109/IMCEC51613.2021.9482226",
language = "English",
series = "IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "797--802",
editor = "Bing Xu",
booktitle = "IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference",
address = "United States",
}