Weapon-target assignment in unreliable peer-to-peer architecture based on adapted artificial bee colony algorithm
Xiaolong LIU, Jinchao LIANG, De-Yu LIU, Riqing CHEN, Shyan-Ming YUAN
Weapon-target assignment in unreliable peer-to-peer architecture based on adapted artificial bee colony algorithm
It is of great significance for headquarters in warfare to address the weapon-target assignment (WTA) problem with distributed computing nodes to attack targets simultaneously from different weapon units. However, the computing nodes on the battlefield are vulnerable to be attacked and the communication environment is usually unreliable. To solve the WTA problems in unreliable environments, this paper proposes a scheme based on decentralized peer-to-peer architecture and adapted artificial bee colony (ABC) optimization algorithm. In the decentralized architecture, the peer computing node is distributed to each weapon units and the packet loss rate is used to simulate the unreliable communication environment. The decisions made in each peer node will be merged into the decision set to carry out the optimal decision in the decentralized system by adapted ABC algorithm. The experimental results demonstrate that the decentralized peer-to-peer architecture perform an extraordinary role in the unreliable communication environment. The proposed scheme preforms outstanding results of enemy residual value (ERV) with the packet loss rate in the range from 0 to 0.9.
weapon-target assignment (WTA) / peer-to-peer / heuristic algorithm / artificial bee colony (ABC)
[1] |
Guo D , Liang Z , Jiang P . Weapon-target assignment for multi-to-multi interception with grouping constraint. IEEE Access, 2019, 7: 34838- 34849
CrossRef
Google scholar
|
[2] |
Cao M , Fang W . Swarm intelligence algorithms for weapon-target assignment in a multilayer defense scenario: a comparative study. Symmetry, 2020, 12 (5): 824
CrossRef
Google scholar
|
[3] |
Sahin A M , Kemal L . Rule-based weapon target assignment on the battlefield. IFAC Proceedings Volumes, 2011, 44 (1): 13600- 13605
CrossRef
Google scholar
|
[4] |
Ni M , Yu Z , Ma F , Wu X . A lagrange relaxation method for solving weapon-target assignment problem. Mathematical Problems in Engineering, 2011, 2011: 1- 10
CrossRef
Google scholar
|
[5] |
Ruan C , Zhou Z , Liu H , Yang H . Task assignment under constraint of timing sequential for cooperative air combat. Journal of Systems Engineering and Electronics, 2016, 27 (4): 836- 844
CrossRef
Google scholar
|
[6] |
Kline A , Ahner D , Hill R . The weapon-target assignment problem. Computers & Operations Research, 2019, 105: 226- 236
CrossRef
Google scholar
|
[7] |
Shojaeifard A . Projection recurrent neural network model: a new strategy to solve weapon-target assignment problem. Neural Processing Letters, 2019, 50 (3): 3045- 3057
CrossRef
Google scholar
|
[8] |
Gao C Q , Kou Y X . Multi-objective weapon target assignment based on D-NSGA-Ⅲ-A. IEEE Access, 2019, 7: 50240- 50254
CrossRef
Google scholar
|
[9] |
Goldberg D E . Genetic algorithm in search optimization and machine learning. In: Proceedings of Genetic Algorithms in Search Optimization and Machine Learning. 1989, 2104- 2116
|
[10] |
Shi Y . Particle swarm optimization: developments, applications and resources. In: Proceedings of the 2001 Congress on Evolutionary Computation. 2001, 81- 86
CrossRef
Google scholar
|
[11] |
Karaboga D , Akay B . A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 2009, 214 (1): 108- 132
CrossRef
Google scholar
|
[12] |
Lee Z J , Su S F , Lee C Y . A genetic algorithm with domain knowledge for weapon-target assignment problems. Journal of the Chinese Institute of Engineers, 2002, 25 (3): 287- 295
CrossRef
Google scholar
|
[13] |
Lee Z J , Su S F , Lee C Y . Efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics. IEEE Transactions on Systems Man, and Cybernetics Part B (Cybernetics), 2003, 33 (1): 113- 121
CrossRef
Google scholar
|
[14] |
Song Z H , Zhu F S , Zhang D L . A heuristic genetic algorithm for solving constrained Weapon-Target Assignment problem. In: Proceedings of IEEE International Conference on Intelligent Computing and Intelligent Systems. 2009, 336- 341
CrossRef
Google scholar
|
[15] |
Zeng X P , Zhu Y L , Nan L . Solving weapon-target assignment problem using discrete particle swarm optimization. In: Proceedings of World Congress on Intelligent Control & Automation. 2006, 3562- 3565
CrossRef
Google scholar
|
[16] |
Yang L , Zhai Z Z , Li Y H , Huang Y T . A multi-information particle swarm optimization algorithm for weapon target assignment of multiple kill vehicle. In: Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics. 2018, 1160- 1165
|
[17] |
Lee Z J , Lee C Y , Su S F . An immunity-based ant colony optimization algorithm for solving weapon-target assignment problem. Applied Soft Computing, 2002, 2 (1): 39- 47
CrossRef
Google scholar
|
[18] |
Karaboga D , Basturk B . A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Journal of Global Optimization, 2007, 39 (3): 459- 471
CrossRef
Google scholar
|
[19] |
Cui L . A novel artificial bee colony algorithm with an adaptive population size for numerical function optimization. Information Science, 2017, 414: 53- 67
CrossRef
Google scholar
|
[20] |
Dean J , Ghemawat S . MapReduce: simplified data processing on large clusters. Communications of the ACM, 2008, 51 (1): 107- 113
CrossRef
Google scholar
|
[21] |
Coulouris D , Dollimore J , Kindberg T , Blair G . Distributed System: Concepts and Design. Pearson Education, 2005
|
[22] |
Lloyd S P , Witsenhausen H S . Weapons allocation is NP-complete. In: Proceedings of Summer Computer Simulation Conference. 1986, 1054- 1058
|
[23] |
Bianchi L , Dorigo M , Gambardella L M , Gutjahr W J . A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing, 2009, 8 (2): 239- 287
CrossRef
Google scholar
|
[24] |
Erik M , Pedersen H , Pedersen M . Good parameters for particle swarm optimization. Hvass Laboratories Technical Report HL1001, 2010, 1- 12
|
/
〈 | 〉 |