DocumentCode :
3154487
Title :
Evolutionary Tabu Search in Task Allocation of Unmanned Aerial Vehicles
Author :
Yan, Ping ; Zheng, Changwen
Author_Institution :
Inst. of software, Chinese Acad. of Sci., Beijing
Volume :
1
fYear :
2006
fDate :
4-6 Oct. 2006
Firstpage :
932
Lastpage :
938
Abstract :
This paper addresses the problem of task allocation problem for a fleet of unmanned aerial vehicles (UAVs). An evolutionary tabu search (TS) algorithm is proposed to search the optimal solution to the task allocation problem. In this algorithm, TS serves as the mutation operator in evolutionary algorithm. Evolutionary computation (EC) gives appropriate initial value and TS helps to find a better solution. In order to meet the requirements of task reallocation in dynamic environment, a partially regroup strategy based on K-mean clustering is employed to find the new solutions in real time while keeping the optimality of results. Our algorithm incorporates domain-specific knowledge and takes into account different kinds of mission constraints. Simulation results validate the feasibility and efficiency of our algorithm
Keywords :
aircraft control; evolutionary computation; pattern clustering; remotely operated vehicles; search problems; K-mean clustering; dynamic environment; evolutionary computation; evolutionary tabu search; mutation operator; task allocation; task reallocation; unmanned aerial vehicles; Application software; Automotive engineering; Clustering algorithms; Costs; Evolutionary computation; Genetic mutations; Military computing; Remotely operated vehicles; Systems engineering and theory; Unmanned aerial vehicles; UAV; evolutionary computation; tabu search; task allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location :
Beijing
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
Type :
conf
DOI :
10.1109/CESA.2006.4281784
Filename :
4281784
Link To Document :
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