원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.7 No.1
2014.01
pp.183-200
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Path planning for uninhabited combat air vehicle (UCAV) is a class of complicated high dimensional optimization problem, which mainly centralizes on path planning considering the different kinds of constrains in the complex environment of war. In order to solve this problem, it is converted to a kind of constrained function optimization problem, and a wolf colony search algorithm based on the complex method is proposed, which combines the complex method with a wolf colony search algorithm, and it solves the problem of UCAV path planning successfully. The experiment results show that our proposed algorithm is feasible and effective to solve the problem of UCAV path planning.
목차
Abstract
1. Introduction
2. UCAV Path Planning Mathematical Model
2.1 Problem description [20]
2.2 Performance indicator
2.3 Threat cost
2.4 Fuel cost
3. CWCA
3.1 Initialize the wolf colony
3.2 Search the quarry
3.3 Besiege the quarry
3.4 Lead the wolf colony to search the quarry based on complex method
3.5 Update the wolf colony
3.6 The pseudo code of CWCA
4. CWCA for Solving UCAV Path Planning
4.1 The steps of UCAV path planning based on CWCA
4.2 The flow chart of UCAV path planning based on CWCA
5. Experiment Simulations
5.1 Influence of control parameters
5.2 Effect of DimensionalityD
5.3 Effect of maximum iterations max t
6. Conclusions
Acknowledgements
References
1. Introduction
2. UCAV Path Planning Mathematical Model
2.1 Problem description [20]
2.2 Performance indicator
2.3 Threat cost
2.4 Fuel cost
3. CWCA
3.1 Initialize the wolf colony
3.2 Search the quarry
3.3 Besiege the quarry
3.4 Lead the wolf colony to search the quarry based on complex method
3.5 Update the wolf colony
3.6 The pseudo code of CWCA
4. CWCA for Solving UCAV Path Planning
4.1 The steps of UCAV path planning based on CWCA
4.2 The flow chart of UCAV path planning based on CWCA
5. Experiment Simulations
5.1 Influence of control parameters
5.2 Effect of DimensionalityD
5.3 Effect of maximum iterations max t
6. Conclusions
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보