IEEE Computational Intelligence Magazine - August 2022 - 53
optimization problems, " in Proc. 2013 IEEE Congr. Evol.
Comput., pp. 2758-2765.
[3] M. N. Omidvar, X. Li, Y. Mei, and X. Yao, " Cooperative
co-evolution with differential grouping for
large scale optimization, " IEEE Trans. Evol. Comput.,
vol. 18, no. 3, pp. 378-393, Jun. 2014, doi: 10.1109/
TEVC.2013.2281543.
[4] F. Sander, H. Zille, and S. Mostaghim, " Transfer strategies
from single- to multi-objective grouping mechanisms, "
in Proc. 2018 Annu. Conf. Genetic Evol. Comput.
Conf., pp. 729-736.
[5] X. Ma et al., " A multiobjective evolutionary algorithm
based on decision variable analyses for multiobjective
optimization problems with large-scale variables, "
IEEE Trans. Evol. Comput., vol. 20, no. 2, pp. 275-298,
Apr. 2016, doi: 10.1109/TEVC.2015.2455812.
[6] X. Zhang, Y. Tian, R. Cheng, and Y. Jin, " A decision
variable clustering-based evolutionary algorithm for
large-scale many-objective optimization, " IEEE Trans.
Evol. Comput., vol. 22, no. 1, pp. 97-112, Feb. 2018, doi:
10.1109/TEVC.2016.2600642.
[7] H. Zille, H. Ishibuchi, S. Mostaghim, and Y. Nojima,
" A framework for large-scale multiobjective optimization
based on problem transformation, " IEEE Trans. Evol.
Comput., vol. 22, no. 2, pp. 260-275, Apr. 2018, doi:
10.1109/TEVC.2017.2704782.
[8] C. He et al., " Accelerating large-scale multiobjective
optimization via problem reformulation, " IEEE Trans.
Evol. Comput., vol. 23, no. 6, pp. 949-961, Dec. 2019,
doi: 10.1109/TEVC.2019.2896002.
[9] H. Qian and Y. Yu, " Solving high-dimensional multi-objective
optimization problems with low effective dimensions, " in
Proc. 31st AAAI Conf. Artif. Intell., 2017, pp. 875-881.
[10] R. Liu, R. Ren, J. Liu, and J. Liu, " A clustering and
dimensionality reduction based evolutionary algorithm
for
[20] Y. Tian, X. Zhang, C. Wang, and Y. Jin, " An evolutionary
algorithm for large-scale sparse multiobjective
optimization problems, " IEEE Trans. Evol. Comput.,
vol. 24, no. 2, pp. 380-393, Apr. 2020, doi: 10.1109/
TEVC.2019.2918140.
[21] Z. Tan, H. Wang, and S. Liu, " Multi-stage dimension
reduction for expensive sparse multi-objective optimization
problems, " Neurocomputing, vol. 440, pp. 159-
174, 2021, doi: 10.1016/j.neucom.2021.01.115.
[22] Y. Tian, C. Lu, X. Zhang, K. C. Tan, and Y. Jin, " Solving
large-scale multi-objective optimization problems with sparse
optimal solutions via unsupervised neural networks, " IEEE
Trans. Cybern., vol. 51, no. 6, pp. 3115-3128, Jun. 2021, doi:
10.1109/TCYB.2020.2979930.
[23] C. A. C. Coello and N. C. Cortés, " Solving multiobjective
optimization problems using an artificial
immune
system, " Genetic Program. Evolvable Mach.,
vol. 6, pp. 163-190, 2005, doi: 10.1007/s10710-005
-6164-x.
[24] E. Zitzler and L. Thiele, " Multiobjective optimization
using evolutionary algorithms-a comparative case
study, " in Proc. 1998 Int. Conf. Parallel Problem Solving
Nature, pp. 292-301.
[25] H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima,
" Reference point
specification in hypervolume
calculation for fair comparison and efficient search, " in
Proc. 2017 Genetic Evol. Comput. Conf., pp. 585-592, doi:
10.1145/3071178.3071264.
[26] Y. Tian, R. Cheng, X. Zhang, M. Li, and Y. Jin,
" Diversity assessment of multi-objective evolutionary
algorithms: Performance metric and benchmark problems
[Research Frontier], " IEEE Comput. Intell. Mag.,
vol. 14, no. 3, pp. 61-74, Aug. 2019, doi: 10.1109/
MCI.2019.2919398.
large-scale multi-objective problems, " Appl. Soft
Comput., vol. 89, p. 106,120, 2020.
[11] Y. Tian, X. Zheng, X. Zhang, and Y. Jin, " Efficient
large-scale multi-objective optimization based on
a competitive swarm optimizer, " IEEE Trans. Cybern.,
vol. 50, no. 8, pp. 3696-3708, Aug. 2020, doi: 10.1109/
TCYB.2019.2906383.
[12] C. He, R. Cheng, and D. Yazdani, " Adaptive
offspring
generation
for
evolutionary
large-scale
multiobjective optimization, " IEEE Trans. Syst., Man,
Cybern. Syst., vol. 52, no. 2, pp. 786-798 Feb 2022,
doi: 10.1109/TSMC.2020.3003926.
[13] W. Hong, K. Tang, A. Zhou, H. Ishibuchi, and X.
Yao, " A scalable indicator-based evolutionary algorithm
for large-scale multiobjective optimization, " IEEE Trans.
Evol. Comput., vol. 23, no. 3, pp. 525-537, Jun. 2018, doi:
10.1109/TEVC.2018.2881153.
[14] H. Chen, R. Cheng, J. Wen, H. Li, and J. Weng,
" Solving large-scale many-objective optimization problems
by covariance matrix adaptation evolution strategy
with scalable small subpopulations, " Inf. Sci., vol. 509, pp.
457-469, 2020, doi: 10.1016/j.ins.2018.10.007.
[15] Y. Jin and B. Sendhoff, " Pareto-based multiobjective
machine learning: An overview and case studies, "
IEEE Trans. Syst., Man, Cybern. C, Appl. Rev.,
vol. 38, no. 3, pp. 397-415, May 2008, doi: 10.1109/
TSMCC.2008.919172.
[16] Y. Tian, S. Yang, L. Zhang, F. Duan, and X. Zhang,
" A surrogate-assisted multiobjective evolutionary algorithm
for large-scale task-oriented pattern mining, " IEEE
Trans. Emerg. Topics Comput. Intell., vol. 3, no. 2, pp. 106-
116, Apr. 2019, doi: 10.1109/TETCI.2018.2872055.
[17] M. Lalou, M. A. Tahraoui, and H. Kheddouci, " The
critical node detection problem in networks: A survey, "
Comput. Sci. Rev., vol. 28, pp. 92-117, 2018, doi:
10.1016/j.cosrev.2018.02.002.
[18] H. Li, Q. Zhang, J. Deng, and B. X. Zong, " A preference-based
multiobjective evolutionary approach for
sparse optimization, " IEEE Trans. Neural Netw. Learn.
Syst., vol. 29, no. 5, pp. 1716-1731, May 2018, doi:
10.1109/TNNLS.2017.2677973.
[19] A. Ponsich, A. L. Jaimes, and C. A. Coello Coello,
" A survey on multiobjective evolutionary algorithms for
the solution of the portfolio optimization problem and
other finance and economics applications, " IEEE Trans.
Evol. Comput., vol. 17, no. 3, pp. 321-344, Jun. 2013, doi:
10.1109/TEVC.2012.2196800.
[27] Y. Tian, C. Lu, X. Zhang, F. Cheng, and Y. Jin, " A
pattern mining based evolutionary algorithm for largescale
sparse
multi-objective optimization problems, "
IEEE Trans. Cybern., early access, Dec. 30, 2020, doi:
10.1109/TCYB.2020.3041325.
[28] M. Li and J. Wei, " A cooperative co-evolutionary
algorithm for large-scale multi-objective optimization
problems, " in Proc. 2018 Annu. Conf. Genetic Evol. Comput.
Conf., pp. 1716-1721.
[29] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, " A
fast and elitist multiobjective genetic algorithm: NSGAII, "
IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182-197,
Apr. 2002, doi: 10.1109/4235.996017.
[30] H. Li and Q. Zhang, " Multiobjective optimization
problems with complicated Pareto sets, MOEA/D and
NSGA-II, " IEEE Trans. Evol. Comput., vol. 13, no. 2, pp.
284-302, Apr. 2009, doi: 10.1109/TEVC.2008.925798.
[31] B. Xue, M. Zhang, and W. N. Browne, " Particle
swarm optimization for feature selection in classification:
A multi-objective approach, " IEEE Trans. Cybern.,
vol. 43, no. 6, pp. 1656-1671, Dec. 2013, doi: 10.1109/
TSMCB.2012.2227469.
[32] R. Cheng, Y. Jin, K. Narukawa, and B. Sendhoff,
" A multiobjective evolutionary algorithm using Gaussian
process-based inverse modeling, " IEEE Trans. Evol.
Comput., vol. 19, no. 6, pp. 838-856, Dec. 2015, doi:
10.1109/TEVC.2015.2395073.
[33] A. Fischer and C. Igel, " An introduction to restricted
Boltzmann machines, " in Proc. Iberoam. Congr. Pattern
Recognit., Springer-Verlag, 2012, pp. 14-36.
[34] P. Vincent, H. Larochelle, Y. Bengio, and P.-A. Manzagol,
" Extracting and composing robust features with
denoising autoencoders, " in Proc. 25th Int. Conf. Mach.
Learn., 2008, pp. 1096-1103, doi: 10.1145/1390156.
1390294.
[35] Y. Tian, R. Liu, X. Zhang, H. Ma, K. C. Tan, and
Y. Jin, " A multi-population evolutionary algorithm for
solving large-scale multi-modal multi-objective optimization
problems, " IEEE Trans. Evol. Comput., vol. 25,
no. 3, pp. 405-418, Jun. 2021, doi: 10.1109/TEVC.2020.
3044711.
[36] M. Li and X. Yao, " Quality evaluation of solution
sets in multiobjective optimisation, " ACM Comput. Surv.,
vol. 52, no. 2, pp. 1-38, 2019, doi: 10.1145/3300148.
[37] K. C. Tan, T. H. Lee, and E. F. Khor, " Evolutionary
algorithms for multi-objective optimization: Performance
assessments and comparisons, " in Proc. 2001 IEEE
Congr. Evol. Comput., pp. 979-986.
[38] S. Bandyopadhyay, S. K. Pal, and B. Aruna, " Multiobjective
GAs, quantitative indices, and pattern classification, "
IEEE Trans. Syst., Man, Cybern. B, Cybern.,
vol. 34, no. 5, pp. 2088-2099, Oct. 2004, doi: 10.1109/
TSMCB.2004.834438.
[39] D. Veldhuizen and G. Lamont, " Evolutionary computation
and convergence to a Pareto front, " in Late
Breaking Papers 1998 Genetic Program. Conf., 1998, pp.
221-228.
[40] J. R. Schott, " Fault tolerant design using single and
multi-criteria genetic algorithms, " M.S. thesis, Department
of Aeronautics and Astronautics, Massachusetts Institute
of Technology, 1995.
[41] J. Wu and S. Azarm, " Metrics for quality assessment
of a multiobjective design optimization solution
set, " J. Mech. Des., vol. 123, no. 1, pp. 18-25, 2001, doi:
10.1115/1.1329875.
[42] Y. Tian, X. Xiang, X. Zhang, R. Cheng, and Y.
Jin, " Sampling reference points on the Pareto fronts of
benchmark multi-objective optimization problems, " in
Proc. 2018 IEEE Congr. Evol. Comput.
[43] A. Zhou, Q. Zhang, and Y. Jin, " Approximating the set
of Pareto-optimal solutions in both the decision and objective
spaces by an estimation of distribution algorithm, " IEEE
Trans. Evol. Comput., vol. 13, no. 5, pp. 1167-1189, Oct. 2009,
doi: 10.1109/TEVC.2009.2021467.
[44] X. Zhang, Y. Tian, R. Cheng, and Y. Jin, " An efficient
approach to nondominated sorting for evolutionary
multiobjective optimization, " IEEE Trans. Evol. Comput.,
vol. 19, no.
2, pp. 201-213, Apr. 2015, doi: 10.1109/
TEVC.2014.2308305.
[45] G. Lizárraga-Lizárraga, A. Hernández-Aguirre,
and S. Botello-Rionda, " G-metric: An M-ary quality
indicator for the evaluation of nondominated sets, "
in Proc. 10th Annu. Conf. Genetic Evol. Comput., 2008,
pp. 665-672.
[46] Q. Zhang and H. Li, " MOEA/D: A multiobjective
evolutionary algorithm based on decomposition, " IEEE
Trans. Evol. Comput., vol. 11, no. 6, pp. 712-731, Dec.
2007, doi: 10.1109/TEVC.2007.892759.
[47] X. Cai, H. Sun, and Z. Fan, " A diversity indicator based
on reference vectors for many-objective optimization, " Inf. Sci.,
vols. 430-431, pp. 467-486, 2018, doi: 10.1016/j.ins.2017.
11.051.
[48] Y. Tian, X. Xiang, X. Zhang, R. Cheng, and Y.
Jin, " Sampling reference points on the Pareto fronts of
benchmark multi-objective optimization problems, " in
Proc. 2018 IEEE Congr. Evol. Comput.
[49] M. Li, S. Yang, and X. Liu, " Diversity comparison of
Pareto front approximations in many-objective optimization, "
IEEE Trans. Cybern., vol. 44, no. 12, pp. 2568-
2584, Dec. 2014, doi: 10.1109/TCYB.2014.2310651.
[50] R. Agrawal and R. Srikant, " Fast algorithms for mining
association rules, " in Proc. Int. Conf. Very Large Data Bases, 1994,
pp. 487-499.
[51] R. A. Rossi and N. K. Ahmed, " The network
data repository with interactive graph analytics and
visualization, " in Proc. 29th AAAI Conf. Artif. Intell.,
2015.
com
[Online]. Available: http://networkrepository.
[52] E. Zitzler and L. Thiele, " Multiobjective evolutionary
algorithms: A comparative case study and the
strength pareto approach, " IEEE Trans. Evol. Comput., vol.
3, no. 4, pp. 257-271, Nov. 1999, doi: 10.1109/4235.
797969.
[53] Y. Tian, R. Cheng, X. Zhang, and Y. Jin, " PlatEMO:
A MATLAB platform for evolutionary multi-objective
optimization [Educational Forum], " IEEE Comput.
Intell. Mag., vol. 12, no. 4, pp. 73-87, Nov. 2017, doi:
10.1109/MCI.2017.2742868.
[54] R. B. Agrawal, K. Deb, and R. B. Agrawal, " Simulated
binary crossover for continuous search space, " Complex
Syst., vol. 9, no. 4, pp. 115-148, 1995.
[55] K. Deb and M. Goyal, " A combined genetic adaptive
search (GeneAS) for engineering design, " Comput. Sci.
Informat., vol. 26, no. 4, pp. 33-45, 1996.
[56] J. Derrac, S. Garcia, D. Molina, and F. Herrera, " A
practical tutorial on the use of nonparametric statistical
tests as a methodology for comparing evolutionary
and swarm intelligence algorithms, " Swarm Evol. Comput.,
vol. 1, no. 1, pp. 3-18, 2011, doi: 10.1016/j.swevo.2011.
02.002.
AUGUST 2022 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 53
http://networkrepository.com
http://networkrepository.com
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