Abstract
The object of multiple Unmanned Aerial Vehicles(UAVs) cooperative reconnaissance is to employ a limit number of UAVs with different capabilities conducting reconnaissance on a set of targets at minimum cost, without violating real world constraints. This problem is a multi-objective optimization problem. We present a Pareto optimality based multi-objective evolutionary algorithm MUCREA to solve the problem. Integer string chromosome representation is designed which ensures that the solution can satisfy the reconnaissance resolution constraints. A construction algorithm is put forward to generate initial feasible solutions for MUCREA, and Pareto optimality based selection with elitism is introduced to generation parent population. Problem specific evolutionary operators are designed to ensure the feasibilities of the children. Simulation results show the efficiency of MUCREA.
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Tian, J., Shen, L. (2006). A Multi-objective Evolutionary Algorithm for Multi-UAV Cooperative Reconnaissance Problem. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_99
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DOI: https://doi.org/10.1007/11893295_99
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46484-6
Online ISBN: 978-3-540-46485-3
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