8 An Introduction to Many-Objective Evolutionary Optimization
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3. J. Arabas, Z. Michalewicz, J. Mulawka, Gavaps-a genetic algorithm with varying population
size, in Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World
Congress on Computational Intelligence, June 1994, vol. 1, pp. 73–78
4. T. Bäck, D.B. Fogel, Z. Michalewicz (eds.) Handbook of Evolutionary Computation, 1st edn.
(IOP Publishing Ltd., Bristol, 1997)
5. T. Bäck, U. Hammel, H.-P. Schwefel, Evolutionary computation: comments on the history and
current state. IEEE Trans. Evol. Comput. 1(1), 3–17 (1997)
6. T.F. Banchoff, D.P. Cervone, An interactive gallery on the internet: “surfaces beyond the third
dimension”. Int. J. Shape Model. 05(01), 7–22 (1999)
7. S. Chand, M. Wagner, Evolutionary many-objective optimization: a quick-start guide. Surv.
Oper. Res. Manage. Sci. 20(2), 35–42 (2015)
8. C.A. Coello Coello, M. Reyes Sierra, A study of the parallelization of a coevolutionary multiobjective evolutionary algorithm, in MICAI 2004: Advances in Artificial Intelligence, ed. by
R. Monroy, G. Arroyo-Figueroa, L.E. Sucar, H. Sossa (Springer, Berlin/Heidelberg, 2004),
pp. 688–697
9. K. Deb, Multi-objective genetic algorithms: problem difficulties and construction of test
problems. Evol. Comput. 7(3), 205–230 (1999)
10. K. Deb, M. Goyal, A combined genetic adaptive search (geneas) for engineering design.
Comput. Sci. Inf. 26, 30–45 (1996)
11. K. Deb, H. Jain, An evolutionary many-objective optimization algorithm using reference-pointbased nondominated sorting approach, part I: solving problems with box constraints. IEEE
Trans. Evol. Comput. 18(4), 577–601 (2014)
12. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic
algorithm: Nsga-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
13. K. Deb, L. Thiele, M. Laumanns, E. Zitzler, Scalable multi-objective optimization test
problems, in Congress on Evolutionary Computation (CEC 2002) (IEEE Press, New York,
2002), pp. 825–830
14. K. Deb, R. Hussein, P. Roy, G. Toscano, Classifying metamodeling methods for evolutionary
multi-objective optimization: first results, in 9th International Conference on Evolutionary
Multi-Criterion Optimization, EMO 2017, New York, NY, vol. 10173 (Springer-Verlag New
York, Inc., New York, 2017), pp. 160–175
15. K.A. DeJong, Evolutionary Computation: A Unified Approach (MIT Press, Cambridge, MA,
2006)
16. M. Ehrgott (ed.) Multicriteria Optimization (Springer, Berlin, 2000)
17. A.E. Eiben, J.E. Smith, Introduction to Evolutionary Computing, 1st edn. Natural Computing
Series (Springer, Berlin, 2003)
18. M. Emmerich, A. Deutz, Multicriteria optimization and decision making principles, algorithms
and case studies (2006)
19. M. Emmerich, N. Beume, B. Naujoks, An emo algorithm using the hypervolume measure as
selection criterion, in Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005 Proceedings, Guanajuato, March 9–11, 2005, ed. by C.A. Coello Coello,
A. Hernández Aguirre, E. Zitzler (Springer, Berlin, 2005), pp. 62–76
20. M. Emmerich, K.C. Giannakoglou, B. Naujoks, Single- and multiobjective evolutionary
optimization assisted by gaussian random field metamodels. IEEE Trans. Evol. Comput. 10(4),
421–439 (2006)
21. M. Farina, P. Amato, On the optimal solution definition for many-criteria optimization problems, in 2002 Annual Meeting of the North American Fuzzy Information
Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622) (2002),
pp. 233–238
22. D.B. Fogel, Nils barricelli - artificial life, coevolution, self-adaptation. IEEE Comput. Intell.
Mag. 1(1), 41–45 (2006)
23. T. Glasmachers, B. Naujoks, G. Rudolph, Start small, grow big? Saving multi-objective
function evaluations, in Parallel Problem Solving from Nature – PPSN XIII, ed. by T. BartzBeielstein, J. Branke, B. Filipiˇ c, J. Smith (Springer International Publishing, Cham, 2014),
pp. 579–588
303
3. J. Arabas, Z. Michalewicz, J. Mulawka, Gavaps-a genetic algorithm with varying population
size, in Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World
Congress on Computational Intelligence, June 1994, vol. 1, pp. 73–78
4. T. Bäck, D.B. Fogel, Z. Michalewicz (eds.) Handbook of Evolutionary Computation, 1st edn.
(IOP Publishing Ltd., Bristol, 1997)
5. T. Bäck, U. Hammel, H.-P. Schwefel, Evolutionary computation: comments on the history and
current state. IEEE Trans. Evol. Comput. 1(1), 3–17 (1997)
6. T.F. Banchoff, D.P. Cervone, An interactive gallery on the internet: “surfaces beyond the third
dimension”. Int. J. Shape Model. 05(01), 7–22 (1999)
7. S. Chand, M. Wagner, Evolutionary many-objective optimization: a quick-start guide. Surv.
Oper. Res. Manage. Sci. 20(2), 35–42 (2015)
8. C.A. Coello Coello, M. Reyes Sierra, A study of the parallelization of a coevolutionary multiobjective evolutionary algorithm, in MICAI 2004: Advances in Artificial Intelligence, ed. by
R. Monroy, G. Arroyo-Figueroa, L.E. Sucar, H. Sossa (Springer, Berlin/Heidelberg, 2004),
pp. 688–697
9. K. Deb, Multi-objective genetic algorithms: problem difficulties and construction of test
problems. Evol. Comput. 7(3), 205–230 (1999)
10. K. Deb, M. Goyal, A combined genetic adaptive search (geneas) for engineering design.
Comput. Sci. Inf. 26, 30–45 (1996)
11. K. Deb, H. Jain, An evolutionary many-objective optimization algorithm using reference-pointbased nondominated sorting approach, part I: solving problems with box constraints. IEEE
Trans. Evol. Comput. 18(4), 577–601 (2014)
12. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic
algorithm: Nsga-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
13. K. Deb, L. Thiele, M. Laumanns, E. Zitzler, Scalable multi-objective optimization test
problems, in Congress on Evolutionary Computation (CEC 2002) (IEEE Press, New York,
2002), pp. 825–830
14. K. Deb, R. Hussein, P. Roy, G. Toscano, Classifying metamodeling methods for evolutionary
multi-objective optimization: first results, in 9th International Conference on Evolutionary
Multi-Criterion Optimization, EMO 2017, New York, NY, vol. 10173 (Springer-Verlag New
York, Inc., New York, 2017), pp. 160–175
15. K.A. DeJong, Evolutionary Computation: A Unified Approach (MIT Press, Cambridge, MA,
2006)
16. M. Ehrgott (ed.) Multicriteria Optimization (Springer, Berlin, 2000)
17. A.E. Eiben, J.E. Smith, Introduction to Evolutionary Computing, 1st edn. Natural Computing
Series (Springer, Berlin, 2003)
18. M. Emmerich, A. Deutz, Multicriteria optimization and decision making principles, algorithms
and case studies (2006)
19. M. Emmerich, N. Beume, B. Naujoks, An emo algorithm using the hypervolume measure as
selection criterion, in Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005 Proceedings, Guanajuato, March 9–11, 2005, ed. by C.A. Coello Coello,
A. Hernández Aguirre, E. Zitzler (Springer, Berlin, 2005), pp. 62–76
20. M. Emmerich, K.C. Giannakoglou, B. Naujoks, Single- and multiobjective evolutionary
optimization assisted by gaussian random field metamodels. IEEE Trans. Evol. Comput. 10(4),
421–439 (2006)
21. M. Farina, P. Amato, On the optimal solution definition for many-criteria optimization problems, in 2002 Annual Meeting of the North American Fuzzy Information
Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622) (2002),
pp. 233–238
22. D.B. Fogel, Nils barricelli - artificial life, coevolution, self-adaptation. IEEE Comput. Intell.
Mag. 1(1), 41–45 (2006)
23. T. Glasmachers, B. Naujoks, G. Rudolph, Start small, grow big? Saving multi-objective
function evaluations, in Parallel Problem Solving from Nature – PPSN XIII, ed. by T. BartzBeielstein, J. Branke, B. Filipiˇ c, J. Smith (Springer International Publishing, Cham, 2014),
pp. 579–588