References¶
We are currently working on a paper. Meanwhile, if you have used our framework for research purposes, you can cite us with:
@misc{pymoo,
title={pymoo: Multi-objective Optimization in Python},
author={Julian Blank and Kalyanmoy Deb},
year={2020},
eprint={2002.04504},
archivePrefix={arXiv},
primaryClass={cs.NE}
}
The reference made in our framework are listed below. The corresponding BibTex is available as well.
- 1
Nikolaus Hansen, Youhei Akimoto, and Petr Baudis. CMA-ES/pycma on Github. Zenodo, DOI:10.5281/zenodo.2559634, February 2019. URL: https://doi.org/10.5281/zenodo.2559634, doi:10.5281/zenodo.2559634.
- 2
Nikolaus Hansen and Andreas Ostermeier. Completely derandomized self-adaptation in evolution strategies. Evol. Comput., 9(2):159–195, June 2001. URL: http://dx.doi.org/10.1162/106365601750190398, doi:10.1162/106365601750190398.
- 3
Nikolaus Hansen. The CMA Evolution Strategy: A Comparing Review, pages 75–102. Springer Berlin Heidelberg, Berlin, Heidelberg, 2006. URL: https://doi.org/10.1007/3-540-32494-1_4, doi:10.1007/3-540-32494-1_4.
- 4
Kenneth Price, Rainer M. Storn, and Jouni A. Lampinen. Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series). Springer-Verlag, Berlin, Heidelberg, 2005. ISBN 3540209506.
- 5
Qingfu Zhang and Hui Li. A multi-objective evolutionary algorithm based on decomposition. IEEE Transactions on Evolutionary Computation, Accepted, 2007.
- 6
J. A. Nelder and R. Mead. A simplex method for function minimization. Computer Journal, 7:308–313, 1965.
- 7
K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. A fast and elitist multiobjective genetic algorithm: nsga-II. Trans. Evol. Comp, 6(2):182–197, April 2002. URL: http://dx.doi.org/10.1109/4235.996017, doi:10.1109/4235.996017.
- 8
Kalyanmoy Deb and Himanshu Jain. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE Transactions on Evolutionary Computation, 18(4):577–601, 2014. doi:10.1109/TEVC.2013.2281535.
- 9
H. Jain and K. Deb. An evolutionary many-objective optimization algorithm using reference-point based nondominated sorting approach, part II: handling constraints and extending to an adaptive approach. IEEE Transactions on Evolutionary Computation, 18(4):602–622, Aug 2014.
- 10
Julian Blank, Kalyanmoy Deb, and Proteek Chandan Roy. Investigating the normalization procedure of NSGA-III. In Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, editors, Evolutionary Multi-Criterion Optimization, 229–240. Cham, 2019. Springer International Publishing.
- 11
Kalyanmoy Deb and J. Sundar. Reference point based multi-objective optimization using evolutionary algorithms. In Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation, GECCO ‘06, 635–642. New York, NY, USA, 2006. ACM. URL: http://doi.acm.org/10.1145/1143997.1144112, doi:10.1145/1143997.1144112.
- 12
Y. Vesikar, K. Deb, and J. Blank. Reference point based NSGA-III for preferred solutions. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 1587–1594. Nov 2018. doi:10.1109/SSCI.2018.8628819.
- 13
H. Seada and K. Deb. A unified evolutionary optimization procedure for single, multiple, and many objectives. IEEE Transactions on Evolutionary Computation, 20(3):358–369, June 2016. doi:10.1109/TEVC.2015.2459718.
- 14
Kalyanmoy Deb and Deb Kalyanmoy. Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Inc., New York, NY, USA, 2001. ISBN 047187339X.
- 15
L. Rachmawati and D. Srinivasan. Multiobjective evolutionary algorithm with controllable focus on the knees of the pareto front. IEEE Transactions on Evolutionary Computation, 13(4):810–824, Aug 2009. doi:10.1109/TEVC.2009.2017515.
- 16
Andrzej P Wierzbicki. The use of reference objectives in multiobjective optimization. In Multiple criteria decision making theory and application, pages 468–486. Springer, 1980.
- 17
Andrzej P. Wierzbicki. A mathematical basis for satisficing decision making. Mathematical Modelling, 3(5):391 – 405, 1982. Special IIASA Issue. URL: http://www.sciencedirect.com/science/article/pii/0270025582900380, doi:https://doi.org/10.1016/0270-0255(82)90038-0.
- 18
David A. Van Veldhuizen and David A. Van Veldhuizen. Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Technical Report, Evolutionary Computation, 1999.
- 19
Hisao Ishibuchi, Hiroyuki Masuda, Yuki Tanigaki, and Yusuke Nojima. Modified distance calculation in generational distance and inverted generational distance. In António Gaspar-Cunha, Carlos Henggeler Antunes, and Carlos Coello Coello, editors, Evolutionary Multi-Criterion Optimization, 110–125. Cham, 2015. Springer International Publishing.
- 20
Carlos A. Coello Coello and Margarita Reyes Sierra. A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm. In Raúl Monroy, Gustavo Arroyo-Figueroa, Luis Enrique Sucar, and Humberto Sossa, editors, MICAI 2004: Advances in Artificial Intelligence, 688–697. Berlin, Heidelberg, 2004. Springer Berlin Heidelberg.
- 21
Carlos M. Fonseca, Luís Paquete, and Manuel López-Ibáñez. An improved dimension sweep algorithm for the hypervolume indicator. In Proceedings of the 2006 Congress on Evolutionary Computation (CEC 2006), pages 1157–1163. IEEE Press, Piscataway, NJ, July 2006. doi:10.1109/CEC.2006.1688440.
- 22
Indraneel Das and J. E. Dennis. Normal-boundary intersection: a new method for generating the pareto surface in nonlinear multicriteria optimization problems. SIAM J. on Optimization, 8(3):631–657, March 1998. URL: http://dx.doi.org/10.1137/S1052623496307510, doi:10.1137/S1052623496307510.
- 23
Kalyanmoy Deb, Sunith Bandaru, and Haitham Seada. Generating uniformly distributed points on a unit simplex for evolutionary many-objective optimization. In Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, editors, Evolutionary Multi-Criterion Optimization, 179–190. Cham, 2019. Springer International Publishing.
- 24
Kalyanmoy Deb, Karthik Sindhya, and Tatsuya Okabe. Self-adaptive simulated binary crossover for real-parameter optimization. In Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, GECCO ‘07, 1187–1194. New York, NY, USA, 2007. ACM. URL: http://doi.acm.org/10.1145/1276958.1277190, doi:10.1145/1276958.1277190.
- 25
To Thanh Binh and Ulrich Korn. Mobes: a multiobjective evolution strategy for constrained optimization problems. In IN PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS (MENDEL97, 176–182. 1997.
- 26
Kalyanmoy Deb and Aravind Srinivasan. Innovization: innovating design principles through optimization. In Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation, GECCO ‘06, 1629–1636. New York, NY, USA, 2006. ACM. URL: http://doi.acm.org/10.1145/1143997.1144266, doi:10.1145/1143997.1144266.
- 27
Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of multiobjective evolutionary algorithms: empirical results. Evolutionary Computation, 8(2):173–195, 2000. URL: https://doi.org/10.1162/106365600568202, arXiv:https://doi.org/10.1162/106365600568202, doi:10.1162/106365600568202.
- 28
H. H. Rosenbrock. An automatic method for finding the greatest or least value of a function. The Computer Journal, 3(3):175–184, mar 1960. URL: https://doi.org/10.1093/comjnl/3.3.175, doi:10.1093/comjnl/3.3.175.
- 29
Kalyanmoy Deb and Mohamed Abouhawwash. An optimality theory-based proximity measure for set-based multiobjective optimization. IEEE Trans. Evolutionary Computation, 20(4):515–528, 2016. URL: https://doi.org/10.1109/TEVC.2015.2483590, doi:10.1109/TEVC.2015.2483590.
- 30
Kalyanmoy Deb, Mohamed Abouhawwash, and Haitham Seada. A computationally fast convergence measure and implementation for single-, multiple-, and many-objective optimization. IEEE Trans. Emerging Topics in Comput. Intellig., 1(4):280–293, 2017. URL: https://doi.org/10.1109/TETCI.2017.2719707, doi:10.1109/TETCI.2017.2719707.