A multi-objective evolutionary algorithm for multi-UAV cooperative reconnaissance problem

Authors:
Jing Tian;Lincheng Shen
Affiliations:
College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, P.R. China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, P.R. China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

Citing 2
Cited 0

Algorithms for the vehicle routing and scheduling problems with time window constraints

Operations Research
Reactive tabu search in unmanned aerial reconnaissance simulations

Proceedings of the 30th conference on Winter simulation

Quantified Score

Hi-index	0.00

Visualization

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 multiobjective 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.