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References
Bader, J., Zitzler, E.: HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization. Evolutionary Computation 19(1), 45–76 (2011)
Beume, N., Naujoks, B., Emmerich, M.: SMS-EMOA: Multiobjective selection based on dominated hypervolume. European Journal of Operational Research 181(3), 1653–1669 (2007)
Bringmann, K., Friedrich, T.: Approximating the least hypervolume contributor: NP-hard in general, but fast in practice. Theoretical Computer Science 425, 104–116 (2012)
Brockhoff, D., Wagner, T., Trautmann, H.: On the properties of the \(R2\) indicator. In: 2012 Genetic and Evolutionary Computation Conference (GECCO 2012), Philadelphia, USA, pp. 465–472. ACM Press, July 2012. ISBN: 978-1-4503-1177-9
Coello Coello, C.A., Cortés, N.C.: Solving Multiobjective Optimization Problems using an Artificial Immune System. Genetic Programming and Evolvable Machines 6(2), 163–190 (2005)
Coello Coello, C.A., Lamont, G.B., Van Veldhuizen, D.A.: Evolutionary Algorithms for Solving Multi-Objective Problems, 2nd edn. Springer, New York (2007). ISBN 978-0-387-33254-3
Coello Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, New York (2002). ISBN 0-3064-6762-3
Das, I., Dennis, J.E.: Normal-boundary intersection: A new method for generating the pareto surface in nonlinear multicriteria optimization problems. SIAM J. on Optimization 8(3), 631–657 (1998)
Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable test problems for evolutionary multiobjective optimization. In: Abraham, A., Jain, L., Goldberg, R. (eds.) Evolutionary Multiobjective Optimization. Theoretical Advances and Applications, pp. 105–145. Springer, London (2005)
Domínguez-Medina, C., Rudolph, G., Schüetze, O., Trautmann, H.: Evenly spaced pareto fronts of quad-objective problems using PSA partitioning technique. In: 2013 IEEE Congress on Evolutionary Computation (CEC 2013), Cancún, México, June 20–23, pp. 3190–3197. IEEE Press (2013). ISBN 978-1-4799-0454-9
Farina, M., Amato, P. : On the optimal solution definition for many-criteria optimization problems. In: Proceedings of the NAFIPS-FLINT International Conference 2002, Piscataway, New Jersey, pp. 233–238. IEEE Service Center, June 2002
Gerstl, K., Rudolph, G., Schütze, O., Trautmann, H. : Finding evenly spaced fronts for multiobjective control via averaging hausdorff-measure. In: The 2011 8th International Conference on Electrical Engineering, Computer Science and Automatic Control (CCE 2011), Mérida, Yucatán, México, pp. 975–980. IEEE Press, October 2011
Gómez, R.H., Coello Coello, C.A.: MOMBI: a new metaheuristic for many-objective optimization based on the \(R2\) indicator. In: 2013 IEEE Congress on Evolutionary Computation (CEC 2013), Cancún, México, June 20–23, pp. 2488–2495. IEEE Press (2013). ISBN 978-1-4799-0454-9
Huband, S., Hingston, P., Barone, L., While, L.: A Review of Multiobjective Test Problems and a Scalable Test Problem Toolkit. IEEE Transactions on Evolutionary Computation 10(5), 477–506 (2006)
Igel, C., Hansen, N., Roth, S.: Covariance Matrix Adaptation for Multi-objective Optimization. Evolutionary Computation 15(1), 1–28 (2007)
Knowles, J., Corne, D.: Properties of an Adaptive Archiving Algorithm for Storing Nondominated Vectors. IEEE Transactions on Evolutionary Computation 7(2), 100–116 (2003)
Menchaca-Mendez, A., Coello Coello, C.A.: A new selection mechanism based on hypervolume and its locality property. In: 2013 IEEE Congress on Evolutionary Computation (CEC 2013), Cancún, México, June 20–23, pp. 924–931. IEEE Press (2013)
Menchaca-Mendez, A., Coello Coello, C.A.: MD-MOEA : a new MOEA based on the maximin fitness function and euclidean distances between solutions. In: 2014 IEEE Congress on Evolutionary Computation (CEC 2014), Beijing, China, July 6–11, pp. 2148–2155. IEEE Press (2014). ISBN 978-1-4799-1488-3
Rodríguez Villalobos, C.A., Coello Coello, C.A.: A new multi-objective evolutionary algorithm based on a performance assessment indicator. In: 2012 Genetic and Evolutionary Computation Conference (GECCO 2012), Philadelphia, USA, pp. 505–512. ACM Press, July 2012. ISBN: 978-1-4503-1177-9
Schütze, O., Esquivel, X., Lara, A., Coello, C.A.: Coello. Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization. IEEE Transactions on Evolutionary Computation 16(4), 504–522 (2012)
Trautmann, Heike, Wagner, Tobias, Brockhoff, Dimo: R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection. In: Nicosia, Giuseppe, Pardalos, Panos (eds.) LION 7. LNCS, vol. 7997, pp. 70–74. Springer, Heidelberg (2013)
Phan, D.H., Suzuki, J.: R2-IBEA: R2 Indicator based evolutionary algorithm for multiobjective optimization. In: 2013 IEEE Congress on Evolutionary Computation (CEC 2013), Cancún, México, June 20–23, pp. 1836–1845. IEEE Press (2013). ISBN 978-1-4799-0454-9
Van Veldhuizen, D.A.: Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. PhD thesis, Department of Electrical and Computer Engineering. Graduate School of Engineering. Air Force Institute of Technology, Wright-Patterson AFB, Ohio, May 1999
Van Veldhuizen, D.A., Lamont, G.B.: Evolutionary computation and convergence to a pareto front. In: Koza, J.R. (ed.) Late Breaking Papers at the Genetic Programming 1998 Conference, Stanford University, California, pp. 221–228. Stanford University Bookstore (1998)
Van Veldhuizen, D.A., Lamont, G.B.: Multiobjective evolutionary algorithm test suites. In: Carroll, J., Haddad, H., Oppenheim, D., Bryant, B., Lamont, G.B. (eds.) Proceedings of the 1999 ACM Symposium on Applied Computing. San Antonio, Texas, pp. 351–357. ACM (1999)
Wagner, Tobias, Trautmann, Heike, Brockhoff, Dimo: Preference Articulation by Means of the R2 Indicator. In: Purshouse, Robin C., Fleming, Peter J., Fonseca, Carlos M., Greco, Salvatore, Shaw, Jane (eds.) EMO 2013. LNCS, vol. 7811, pp. 81–95. Springer, Heidelberg (2013)
Zhang, Q., Li, H.: MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Transactions on Evolutionary Computation 11(6), 712–731 (2007)
Zitzler, Eckart, Künzli, Simon: Indicator-Based Selection in Multiobjective Search. In: Yao, Xin, Burke, Edmund K., Lozano, José A., Smith, Jim, Merelo-Guervós, Juan Julián, Bullinaria, John A., Rowe, Jonathan E., Tiňo, Peter, Kabán, Ata, Schwefel, Hans-Paul (eds.) PPSN 2004. LNCS, vol. 3242, pp. 832–842. Springer, Heidelberg (2004)
Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M.: Grunert da Fonseca, V.: Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation 7(2), 117–132 (2003)
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Menchaca-Mendez, A., Coello Coello, C.A. (2015). GD-MOEA: A New Multi-Objective Evolutionary Algorithm Based on the Generational Distance Indicator. In: Gaspar-Cunha, A., Henggeler Antunes, C., Coello, C. (eds) Evolutionary Multi-Criterion Optimization. EMO 2015. Lecture Notes in Computer Science(), vol 9018. Springer, Cham. https://doi.org/10.1007/978-3-319-15934-8_11
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