Task Assignment for Multivehicle Systems Based on Collaborative Neurodynamic Optimization
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Article number | 8741205 |
Pages (from-to) | 1145-1154 |
Journal / Publication | IEEE Transactions on Neural Networks and Learning Systems |
Volume | 31 |
Issue number | 4 |
Online published | 19 Jun 2019 |
Publication status | Published - Apr 2020 |
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Abstract
This paper addresses task assignment (TA) for multivehicle systems. Multivehicle TA problems are formulated as a combinatorial optimization problem and further as a global optimization problem. To fulfill heterogeneous tasks, cooperation among heterogeneous vehicles is incorporated in the problem formulations. A collaborative neurodynamic optimization approach is developed for solving the TA problems. Experimental results on four types of TA problems are discussed to substantiate the efficacy of the approach.
Research Area(s)
- Multivehicle systems, neurodynamic optimization, task assignment (TA)
Citation Format(s)
Task Assignment for Multivehicle Systems Based on Collaborative Neurodynamic Optimization. / Wang, Jiasen; Wang, Jun; Che, Hangjun.
In: IEEE Transactions on Neural Networks and Learning Systems, Vol. 31, No. 4, 8741205, 04.2020, p. 1145-1154.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review