IEEE Computational Intelligence Magazine - August 2022 - 65

Acknowledgments
The authors acknowledge the support
of The Volkswagen Foundation to carry
out this research.
References
[1] S. Flaxman et al., " Estimating the effects of nonpharmaceutical
interventions on COVID-19 in Europe, "
Nature, vol. 584, no. 7820, pp. 257-261, 2020.
[2] N. Christakis, Apollo's Arrow: The Profound and Enduring
Impact of Coronavirus on the Way We Live. Little,
Brown, 2020 .
[3] M. McKee and D. Stuckler, " If the world fails to protect
the economy, COVID-19 will damage health not just
now but also in the future, " Nature Med., vol. 26, no. 5,
pp. 640-642, 2020, doi: 10.1038/s41591-020-0863-y.
[4] R. Miikkulainen, O. Francon, E. Meyerson, X. Qiu,
E. Canzani, and B. Hodjat, " From prediction to prescription:
evolutionary optimization of non-pharmaceutical
interventions in the COVID-19 pandemic, " IEEE Trans.
Evol. Comput., vol. 25, no. 2, pp. 386-401, Apr. 2021, doi:
10.1109/TEVC.2021.3063217.
[5] V. S. Tseng, J. Jia-Ching Ying, S. T. Wong, D. J.
Cook, and J. Liu, " Computational
intelligence techniques
for combating COVID-19: A survey, " IEEE Comput.
Intell. Mag., vol. 15, no. 4, pp. 10-22, Nov. 2020, doi:
10.1109/MCI.2020.3019873.
[6] A. Yousefpour, H. Jahanshahi, and S. Bekiros, " Optimal
policies for control of the novel coronavirus disease
(COVID-19) outbreak, " Chaos, Solitons Fractals, vol. 136,
p. 109,883, Jan. 2020.
[7] R. Salgotra, A. Moshaiov, T. Seidelmann, D. Fischer,
and S. Mostaghim, " Optimal control policies to address
the pandemic health-economy dilemma, " in Proc. 2021
IEEE Congr. Evol. Comput. (CEC), pp. 720-727, doi:
10.1109/CEC45853.2021.9504758.
[8] W. Kermack and A. McKendrick, " A contribution to
the mathematical theory of epidemics, " in Proc. Roy. Soc.
London Series A, Containing Papers Math. Phys. Character,
vol. 115, no. 772, pp. 700-721, 1927.
[9] A. Mojeeb, I. K. Adu, and C. Yang, " A simple
seir mathematical model of malaria transmission, "
Asia Res. J. Math., pp. 1-27, 2017, doi: 10.9734/AR
JOM/2017/37471.
[10] S. Lai et al., " Effect of non-pharmaceutical interventions
to contain COVID-19 in China, " Nature, vol. 585,
no. 7825, pp. 410-413, 2020.
[11] S. He, Y. Peng, and K. Sun, " SEIR modeling of the
COVID-19 and its dynamics, " Nonlinear Dyn., vol. 101,
no. 3, pp. 1667-1680, 2020 , doi: 10.1007/s11071-020
-05743-y.
[12] C. Colas et al., " EpidemiOptim: A toolbox for the
optimization of control policies in epidemiological models, "
2020, arXiv: 2010.04452.
[13] H. Wulkow, T. O. Conrad, N. D. Conrad, S. A.
Müller, K. Nagel, and C. Schütte, " Prediction of COVID-19
spreading and optimal coordination of countermeasures:
From microscopic to macroscopic models to
Pareto fronts, " PLoS One, vol. 16, pp. 1-29, Apr. 4, 2021,
doi: 10.1371/journal.pone.0249676.
[14] N. Perra, " Non-pharmaceutical interventions during
the COVID-19 pandemic: A review, " Phys. Rep., vol. 913,
pp. 1-52, 2021, doi: 10.1016/j.physrep.2021.02.001.
[15] J. Panovska-Griffiths, C. Kerr, W. Waites, and R.
Stuart, " Mathematical modeling as a tool for policy decision
making: Applications to the COVID-19 pandemic, "
pp. 291-326, Jan. 2021.
[16] H. Rahmandad and J. Sterman, " Heterogeneity and
network structure in the dynamics of diffusion: Comparing
agent-based and differential equation models, " Manage.
Sci., vol. 54, no. 5, pp. 998-1014, 2008, doi: 10.1287/
mnsc.1070.0787.
[17] J. M. Carcione, J. E. Santos, C. Bagaini, and J. Ba,
" A simulation of a COVID-19 epidemic based on a
deterministic seir model, " Frontiers Public Health, vol. 8,
2020, doi: 10.3389/fpubh.2020.00230.
[18] 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.
[19] 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.
[20] H. Zille, " Large-scale multi-objective optimisation:
New approaches and a classification of the state-of-theart, "
Ph.D. dissertation, 2019.
[21] K. Deb and H. Jain, " An evolutionary many-objective
optimization algorithm using reference-point-based
nondominated sorting approach, Part I: Solving problems
with box constraints, " IEEE Trans. Evol. Comput.,
vol. 18, no. 4, pp. 577-601, Aug. 2014, doi: 10.1109/
TEVC.2013.2281535.
[22] S. Huband, P. Hingston, L. While, and L. Barone,
" An evolution strategy with probabilistic mutation for
multi-objective optimisation, " in Proc. 2003 Congr. Evol.
Comput., CEC '03, vol. 4, pp. 2284-2291.
TAP.
CONNECT.
NETWORK.
SHARE.
Connect to IEEE-no matter where you are-with the IEEE App.
Stay up-to-date
with the latest news
Read and download
your IEEE magazines
Schedule, manage, or
join meetups virtually
Create a personalized
experience
Get geo and interest-based
recommendations
Locate IEEE members by location,
interests, and affiliations
AUGUST 2022 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 65
IEEE Computational Intelligence Magazine - August 2022

Table of Contents for the Digital Edition of IEEE Computational Intelligence Magazine - August 2022
