1 |
SHI Y J, TENG H F, LI Z Q. Cooperative co-evolutionary differential evolution for function optimization[C]//Proceedings of the 1st International Conference on Natural Computation. Berlin, Germany: Springer, 2005: 1080-1088.
|
2 |
OMIDVAR M N, LI X D, YAO X. Smart use of computational resources based on contribution for cooperative co-evolutionary algorithms[C]//Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation. New York, USA: ACM Press, 2011: 1115-1122.
|
3 |
KESHK M, SINGH H, ABBASS H. Automatic estimation of differential evolution parameters using hidden Markov models. Evolutionary Intelligence, 2018, 10(3): 77- 93.
|
4 |
DENG L B, LI C L, SUN G J. An adaptive dimension level adjustment framework for differential evolution. Knowledge-Based Systems, 2020, 206, 106388.
doi: 10.1016/j.knosys.2020.106388
|
5 |
MALLIPEDDI R, SUGANTHAN P N, PAN Q K, et al. Differential evolution algorithm with ensemble of parameters and mutation strategies. Applied Soft Computing, 2011, 11(2): 1679- 1696.
doi: 10.1016/j.asoc.2010.04.024
|
6 |
SUN G J, WU Y R, DENG L B, et al. Elite representative based individual adaptive regeneration framework for differential evolution. IEEE Access, 2020, 8, 61226- 61245.
doi: 10.1109/ACCESS.2020.2983840
|
7 |
SEMNANI A, KAMYAB M, REKANOS I T. Reconstruction of one-dimensional dielectric scatterers using differential evolution and particle swarm optimization. IEEE Geoscience and Remote Sensing Letters, 2009, 6(4): 671- 675.
doi: 10.1109/LGRS.2009.2023246
|
8 |
王磊, 林鸿飞, 滕弘飞. 并行协同差异进化算法研究. 计算机工程, 2012, 38(4): 182-184, 190.
URL
|
|
WANG L, LIN H F, TENG H F. Research on parallel cooperative coevolutionary differential evolution algorithm. Computer Engineering, 2012, 38(4): 182-184, 190.
URL
|
9 |
TSENG L Y, CHEN C. Multiple trajectory search for large scale global optimization[C]//Proceedings of the IEEE World Congress on Computational Intelligence. Washington D. C., USA: IEEE Press, 2008: 3052-3059.
|
10 |
MANIEZZO V, GAMBARDELLA L M, de LUIGI F. Ant colony optimization[M]//ONWUBOLU G C, BABU B V. New optimization techniques in engineering. Berlin, Germany: Springer, 2004: 101-121.
|
11 |
MOLINA D, LOZANO M, SÁNCHEZ A M, et al. Memetic algorithms based on local search chains for large scale continuous optimisation problems: MA-SSW-Chains. Soft Computing: A Fusion of Foundations, Methodologies and Applications, 2011, 15(11): 2201- 2220.
|
12 |
YEN G G, DANESHYARI M. Diversity-based information exchange among multiple swarms in particle swarm optimization. International Journal of Computational Intelligence and Applications, 2008, 7(1): 57- 75.
doi: 10.1142/S1469026808002144
|
13 |
MOHAPATRA P, DAS K N, ROY S. A modified competitive swarm optimizer for large scale optimization problems. Applied Soft Computing, 2017, 59(C): 340- 362.
|
14 |
MOHAPATRA P, DAS K N, ROY S. Inherited competitive swarm optimizer for large-scale optimization problems[M]//YADAV N, YADAV A, BANSAL J, et al. Harmony search and nature inspired optimization algorithms. Berlin, Germany: Springer, 2019: 85-95.
|
15 |
CHENG R, JIN Y C. A competitive swarm optimizer for large scale optimization. IEEE Transactions on Cybernetics, 2015, 45(2): 191- 204.
doi: 10.1109/TCYB.2014.2322602
|
16 |
COLLANGE G, REYNAUD S, HANSEN N. Covariance matrix adaptation evolution strategy for multidisciplinary optimization of expendable launcher family[C]//Proceedings of the 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference. Washington D. C., USA: IEEE Press, 2010: 9088.
|
17 |
刘方洁. 基于分组与局部搜索的大规模全局优化新算法[D]. 西安: 西安电子科技大学, 2017.
|
|
LIU F J. New algorithms based on decomposing and local search for large scale global optimization[D]. Xi'an: Xidian University, 2017. (in Chinese)
|
18 |
YANG Z Y, TANG K, YAO X. Large scale evolutionary optimization using cooperative coevolution. Information Sciences: An International Journal, 2008, 178(15): 2985- 2999.
doi: 10.1016/j.ins.2008.02.017
|
19 |
OMIDVAR M N, LI X D, MEI Y, et al. Cooperative co-evolution with differential grouping for large scale optimization. IEEE Transactions on Evolutionary Computation, 2014, 18(3): 378- 393.
doi: 10.1109/TEVC.2013.2281543
|
20 |
SUN Y, KIRLEY M, HALGAMUGE S K. Extended differential grouping for large scale global optimization with direct and indirect variable interactions[C]//Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. New York, USA: ACM Press, 2015: 313-320.
|
21 |
ZHANG X Y, GONG Y J, LIN Y, et al. Dynamic cooperative coevolution for large scale optimization. IEEE Transactions on Evolutionary Computation, 2019, 23(6): 935- 948.
doi: 10.1109/TEVC.2019.2895860
|
22 |
WANG Y, CAI Z X, ZHANG Q F. Differential evolution with composite trial vector generation strategies and control parameters. IEEE Transactions on Evolutionary Computation, 2011, 15(1): 55- 66.
doi: 10.1109/TEVC.2010.2087271
|
23 |
LI X, TANG K, OMIDVAR M N, et al. Benchmark functions for the CEC'2013 special session and competition on large-scale global optimization. Gene, 2013, 7(33): 8.
|
24 |
ZHANG J Q, SANDERSON A C. JADE: adaptive differential evolution with optional external archive. IEEE Transactions on Evolutionary Computation, 2009, 13(5): 945- 958.
doi: 10.1109/TEVC.2009.2014613
|
25 |
YANG Z Y, TANG K, YAO X. Self-adaptive differential evolution with neighborhood search[C]//Proceedings of the IEEE World Congress on Computational Intelligence. Washington D. C., USA: IEEE Press, 2008: 1110-1116.
|