원문정보
보안공학연구지원센터(IJGDC)
International Journal of Grid and Distributed Computing
Vol.8 No.3
2015.06
pp.135-144
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Multiple Unmanned Underwater Vehicles Is a typical combinatorial optimization problem, to achieve multiple AUV, coordinated, collaborative tasks to complete complex jobs subsea. Through analyzing the ant colony optimization algorithm, the paper proposed An Meta-heuristic ant colony optimization algorithm the Implementation to solve the multi AUVs to achieve the task allocation problem, and had simulation test based on the consolidated analyze the advantages of multiple unmanned underwater vehicle .results show that the ant colony optimization algorithms in solving multi-task allocation problem of multiple unmanned underwater vehicle showed a good performance.
목차
Abstract
1. Introduction
2. Ant Colony Optimization
2.1. Aco Meta-Heuristic Algorithm
2.2. ACO Mathematical Model
3. Multi- Tasking AUVS
3.1. Generalized Assignment
3.2. Multiple AUVS Collaborative Planning Assignments
4. Experimental Results and Analysis
4.1. Multi-Tasking Comprehensive Superiority of AUVS
4.2. Multi-Tasking AUVS Meta-Heuristic Ant Colony Algorithm
4.3. Simulation
5. Conclusions
Acknowledgements
References
1. Introduction
2. Ant Colony Optimization
2.1. Aco Meta-Heuristic Algorithm
2.2. ACO Mathematical Model
3. Multi- Tasking AUVS
3.1. Generalized Assignment
3.2. Multiple AUVS Collaborative Planning Assignments
4. Experimental Results and Analysis
4.1. Multi-Tasking Comprehensive Superiority of AUVS
4.2. Multi-Tasking AUVS Meta-Heuristic Ant Colony Algorithm
4.3. Simulation
5. Conclusions
Acknowledgements
References
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