Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (4): 10071019.doi: 10.23919/JSEE.2023.000102
• CONTROL THEORY AND APPLICATION • Previous Articles
Yang ZHAO(), Jicheng LIU(), Ju JIANG(), Ziyang ZHEN()
Received:
20210307
Online:
20230818
Published:
20230828
Contact:
Yang ZHAO
Email:zy@nuaa.edu.cn;ljc_uav@nuaa.edu.com;jiangju@nuaa.edu.cn;zhenziyang@nuaa.edu.cn
About author:
Supported by:
Yang ZHAO, Jicheng LIU, Ju JIANG, Ziyang ZHEN. Shuffled frog leaping algorithm with nondominated sorting for dynamic weapontarget assignment[J]. Journal of Systems Engineering and Electronics, 2023, 34(4): 10071019.
Table 1
Parameters of Cases I?IV"
Parameter  Value  Type 
  Integer 
  Integer 
  Integer 
  Integer 
 1  Integer 
  Integer 
  Integer 
 where  Float 
Table 2
Main effects of EX1"
      
(5,60)  (38.24,10.27)  (0.00531,0.00507)  16.2931  1.4682  63.0241  0.3184 
(10,30)  (37.37,11.51)  (0.00406,0.00401)  15.6742  0.9257  58.2852  0.7627 
(15,20)  (37.12,12.01)  (0.00352,0.00337)  14.7203  0.5060  52.7503  1.9241 
(20,15)  (37.13,11.79)  (0.00347,0.00364)  14.9268  0.7401  58.9511  1.7956 
(30,10)  (37.45,11.23)  (0.00509,0.00498)  15.6472  0.8364  60.2047  0.6507 
(60,5)  (38.03,11.02)  (0.00646,0.00632)  15.9356  1.2679  62.6059  0.3166 
Table 3
Comprehensive performance of the combination pools"
P=150  P=200  P=500  
      
(5,30)  0.2668  (5,40)  1.4502  (10,50)  4.9341  
(10,15)  0.2955  (10,20)  1.5884  (20,25)  5.1755  
(15,10)  0.3031  (20,10)  1.6032  (25,20)  5.3022  
(30,5)  0.2764  (40,5)  1.4794  (50,10)  4.9816 
Table 4
Main effects of EX2"
Case  Criteria   
   
2.0  6.0  10.0  2.0  6.0  10.0  2.0  6.0  10.0  
II   8.2473  8.2472  8.2473  8.2461  8.2458  8.2460  8.2470  8.2472  8.2472  
 4.8051  4.8050  4.8055  4.8079  4.8082  4.8068  4.8081  4.8112  4.8078  
 9.6005  9.1317  8.9053  9.5224  9.0127  8.9050  9.6732  9.1260  9.1071  
 18.5207  15.3214  15.8553  17.0524  13.3285  16.5227  14.0952  13.4100  16.2571  
 13.4931  18.4212  19.3138  11.7050  21.5326  16.6947  15.4371  19.0545  18.9267  
III   37.2723  37.2715  37.2771  37.1365  37.1361  37.1473  37.1642  37.1637  37.1810  
 12.0548  12.1036  12.0872  12.1429  12.2550  12.2546  12.2510  12.2649  12.2588  
 14.3106  13.5501  13.1864  13.3601  12.9197  13.0985  14.6062  13.0089  13.4272  
 65  59  61  62  55  56  66  62  62  
 0.4060  0.5009  0.4978  0.5329  0.6220  0.6212  0.4576  0.0538  0.5296 
Table 5
Main effects of EX3"
Parameter  Binh1  Fonseca2  Poloni  
NSFLA  NSGAII  NSFLA  NSGAII  NSFLA  NSGAII  
 0.00015  0.00020  0.00012  0.00077  0.00038  0.00170  
 6.68508  7.00131  5.24771  5.78068  6.52404  7.13399  
 0.02091  0.02417  0.00096  0.00154  0.11474  0.13550 
1  KLINE A, AHNER D, HILL R The weapontarget assignment problem. Computers & Operations Research, 2019, 105 (1): 226 236. 
2 
LEE Z J, LEE C Y, SU S F An immunitybased ant colony optimization algorithm for solving weapontarget assignment problem. Applied Soft Computing, 2002, 2 (1): 39 47.
doi: 10.1016/S15684946(02)000273 
3 
XIN B, CHEN J, ZHANG J, et al Efficient decision makings for dynamic weapontarget assignment by virtual permutation and tabu search heuristics. IEEE Trans. on Systems Man and Cybernetics Part CApplications and Reviews, 2010, 40 (6): 649 662.
doi: 10.1109/TSMCC.2010.2049261 
4  ZHANG Y, YANG R N, ZUO J L, et al Weapontarget assignment based on decompositionbased evolutionary multiobjective optimization algorithms. Systems Engineering and Electronics, 2014, 36 (12): 2435 2441. 
5  LI N, HUAI W Q, WANG S D The solution of target assignment problem in command and control decisionmaking behaviour simulation. Enterprise Information Systems, 2016, 11 (7): 1059 1077. 
6 
AHUJA R K, KUMAR A, JHA K C, et al Exact and heuristic algorithms for the weapontarget assignment problem. Operations Research, 2007, 55 (6): 1136 1146.
doi: 10.1287/opre.1070.0440 
7  KARASAKAL O, OZDEMIREL NE, KANDILLER L Antiship missile defense for a naval task group. Naval Research Logistics, 2011, 58 (3): 305 322. 
8 
KORSAH G A, STENTZ A, DIAS M B A comprehensive taxonomy for multirobot task allocation. International Journal of Robotics Research, 2013, 32 (12): 1495 1512.
doi: 10.1177/0278364913496484 
9 
LUO L, CHAKRABORTY N, SYCARA K Provablygood distributed algorithm for constrained multirobot task assignment for grouped tasks. IEEE Trans. on Robotics, 2015, 31 (1): 19 30.
doi: 10.1109/TRO.2014.2370831 
10  LLOYD S P, WITSENHAUSEN H S. Weapons allocation is NPcomplete. Proc. of the Summer Computer Simulation Conference, 1986: 1054−1061. 
11  SAHIN M A, LEBLEBICIOGLU K Approximating the optimal mapping for weapon target assignment by fuzzy reasoning. Information Sciences, 2014, 255 (1): 30 44. 
12  CHANG T Q, KONG D P, HAO N, et al Solving the dynamic weapon target assignment problem by an improved artificial bee colony algorithm with heuristic factor initialization. Applied Soft Computing, 2018, 70 (1): 845 863. 
13  ZHAO Y, CHEN Y F, ZHEN Z Y, et al Multiweapon multitarget assignment based on hybrid genetic algorithm in uncertain environment. International Journal of Advanced Robotic Systems, 2020, 17 (2): 1054 1058. 
14  LI X, LUO J, CHEN M R, et al An improved shuffled frogleaping algorithm with extremal optimization for continuous optimization. Information Sciences, 2012, 192 (1): 143 151. 
15 
CAI H P, LIU J X, CHEN Y W, et al Survey of the research on dynamic weapontarget assignment problem. Journal of Systems Engineering and Electronics, 2006, 17 (3): 559 565.
doi: 10.1016/S10044132(06)600972 
16  NI M F, YU Z K, MA F, et al A Lagrange relaxation method for solving weapontarget assignment problem. Mathematical Problems in Engineering, 2011, 4 (1): 264 265. 
17  SAHIN M, LEBLEBICIOGLU K. Rulebased weapon target assignment on the battlefield. Proc. of the 18th IFAC World Congress, 2011: 13600−13605. 
18 
DAVIS M T, ROBBINS M J, LUNDAY B J Approximate dynamic programming for missile defense interceptor fire control. European Journal of Operational Research, 2017, 259 (3): 873 886.
doi: 10.1016/j.ejor.2016.11.023 
19 
BOARDMAN N T, LUNDAY B J, ROBBINS M J Heterogeneous surfacetoair missile defense battery location: a game theoretic approach. Journal of Heuristics, 2017, 23 (6): 417 447.
doi: 10.1007/s1073201793500 
20  WANG S H, YANG Q S, WANG R H, et al Particle swarm optimization based weapontarget assignment for attacking ground targets. Electronics Optics & Control, 2017, 24 (3): 36 40. 
21  MEI Z J, PENG Z H, ZHANG X L. Optimal dynamic weapontarget assignment based on receding horizon control heuristic. Proc. of the 13th IEEE International Conference on Control & Automation, 2017: 876−881. 
22  GAO C Q, KOU Y X, LI Y, et al. Multiobjective weapon target assignment based on DNSGAIIIA. IEEE Access, 2019, 7: 50240−50254. 
23  STEUER R E. Multiple criteria optimization: theory, computation, and application. Malabar: Krieger, 1988. 
24 
ZHA W Z, CHEN J, PENG Z H Dynamic multiteam antagonistic games model with incomplete information and its application to multiUAV. IEEE/CAA Journal of Automatica Sinica, 2015, 2 (1): 74 84.
doi: 10.1109/JAS.2015.7032908 
25  WANG Y, GARCIA E, CASBEER D, et al. Cooperative control of multiagent systems: theory and applications. New York: John Wiley & Sons, 2017. 
26 
OSYCZKA A An approach to multicriterion optimization problems for engineering design. Computer Methods in Applied Mechanics and Engineering, 1978, 15 (3): 309 333.
doi: 10.1016/00457825(78)900464 
27  SARABI J A, ARAABI B N How to decide when the sources of evidence are unreliable: a multicriteria discounting approach in the DempsterShafer theory. Information Sciences, 2018, 448 (1): 233 248. 
28  ZHOU D Y, PAN Q, ZHANG K. An improved discrete shuffled frog leaping algorithm for cooperative multitarget assignment of BVR air combat. Proc. of the IEEE International Conference on Signal Processing, Communications and Computing, 2014: 686−691. 
29  LAI C M, WU T H Simplified swarm optimization with initialization scheme for dynamic weapontarget assignment problem. Applied Soft Computing, 2019, 82, 105542. 
30 
EUSUFF M, LANSEY K Optimization of water distribution network design using the shuffled frog leaping algorithm. Journal of Water Resources Planning and Management, 2003, 129 (3): 210 225.
doi: 10.1061/(ASCE)07339496(2003)129:3(210) 
31 
EUSUFF M, LANSEY E, PASHA F Shuffled frogleaping algorithm: a memetic metaheuristic for discrete optimization. Engineering Optimization, 2006, 38 (2): 129 154.
doi: 10.1080/03052150500384759 
32 
ROY P, CHAKRABARTI A Modified shuffled frog leaping algorithm with genetic algorithm crossover for solving economic load dispatch problem with valvepoint effect. Applied Soft Computing, 2013, 13 (11): 4244 4252.
doi: 10.1016/j.asoc.2013.07.006 
33 
FETTAKA S, THIBAULT J, GUPTA Y A new algorithm using front prediction and NSGAII for solving two and threeobjective optimization problems. Optimization and Engineering, 2015, 16 (4): 713 736.
doi: 10.1007/s1108101492719 
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