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Multi-sensor and multi-target task allocation method based on improved firefly algorithm
Author(s): Pengxiang Wang; Feng Yang; Yizhai Zhang; Litao Zhang
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Paper Abstract

Sensor task allocation plays a great role in military, environmental science, medical health, transportation and other fields. In order to make rational use of limited sensor resources, a multi-sensor multi-target task allocation method based on an improved firefly algorithm (FA) is proposed. In the algorithm, the initial position of firefly individual in firefly algorithm is optimized to speed up the search optimization procedure. In the process of constructing efficiency function, position constraints, sensor monitoring ability constraints and target threat degree constraints are considered comprehensively, leading to a more realistic multi-sensor multi-target task allocation algorithm. The analytic hierarchy process (AHP) is used to construct the target threat measure. The simulation results show that the proposed algorithm is more efficient than the standard particle swarm optimization algorithm (PSO) and the standard FA, that is, the sensor task allocation is more reasonable, and the task allocation time cost is also shorter than the other two algorithms.

Paper Details

Date Published: 31 August 2018
PDF: 6 pages
Proc. SPIE 10835, Global Intelligence Industry Conference (GIIC 2018), 108350P (31 August 2018); doi: 10.1117/12.2503827
Show Author Affiliations
Pengxiang Wang, Northwestern Polytechnical Univ. (China)
Ministry of Education (China)
Feng Yang, Northwestern Polytechnical Univ. (China)
Ministry of Education (China)
Yizhai Zhang, Northwestern Polytechnical Univ. (China)
Ministry of Education (China)
Litao Zhang, Northwestern Polytechnical Univ. (China)
Ministry of Education (China)


Published in SPIE Proceedings Vol. 10835:
Global Intelligence Industry Conference (GIIC 2018)
Yueguang Lv, Editor(s)

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