pymoo
Latest Version: pymoo==0.3.1

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,
    author = {Julian Blank and Kalyanmoy Deb},
    title = {pymoo - {Multi-objective Optimization in Python}},
    howpublished = {https://pymoo.org}
}

The reference made in our framework are listed below. The corresponding BibTex is available as well.


1

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.

2

Qingfu Zhang and Hui Li. A multi-objective evolutionary algorithm based on decomposition. IEEE Transactions on Evolutionary Computation, Accepted, 2007.

3

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.

4

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.

5

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.

6

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.

7

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.

8

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.

9

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.

10

Kalyanmoy Deb and Deb Kalyanmoy. Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Inc., New York, NY, USA, 2001. ISBN 047187339X.

11

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.

12

Andrzej P Wierzbicki. The use of reference objectives in multiobjective optimization. In Multiple criteria decision making theory and application, pages 468–486. Springer, 1980.

13

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.

14

David A. Van Veldhuizen and David A. Van Veldhuizen. Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Technical Report, Evolutionary Computation, 1999.

15

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.

16

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.

17

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.

18

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.

19

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.

20

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.

21

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.

22

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.

23

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.

24

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.