Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2018 | OriginalPaper | Chapter

A Many-Objective Evolutionary Algorithm with Reference Point-Based and Vector Angle-Based Selection

Authors : Chen-Yu Lee, Jia-Fong Yeh, Tsung-Che Chiang

Published in: Genetic and Evolutionary Computing

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this paper we proposed a many-objective evolutionary algorithm by combining the reference point-based selection in NSGA-III and the vector angle-based selection in VaEA. Performance of the proposed algorithm is verified by testing on the negative version of four DTLZ functions. The proposed algorithm is better than NSGA-III and is comparable to VaEA in terms of IGD. Besides, the proposed algorithm is more robust and can expand the front better.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter Freeway Travel Time Prediction by Using the GA-Based Hammerstein Recurrent Neural Network
Literature
1.
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and eitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 181–192 (2002). [NSGA-II]CrossRef
2.
Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the strength Pareto evolutionary algorithm. Technical Report 103, Department of Electrical Engineering, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland (2001). [SPEA2]
3.
Ishibuchi, H., Tsukamoto, N., Nojima, Y.: Evolutionary many-objective optimization: a short review. In: Proceedings of the IEEE Conference on Evolutionary Computation, pp. 2419–2426 (2008)
4.
Deb, K., Jain, H.: An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, part I: solving problems with box constraints. IEEE Trans. Evol. Comput. 18(4), 577–601 (2014). [NSGA-III]CrossRef
5.
Zhang, Q., Li, H.: MOEA/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712–731 (2007). [MOEA/D]CrossRef
6.
Li, K., Deb, K., Zhang, Q., Kwong, S.: An evolutionary many-objective optimization algorithm based on dominance and decomposition. IEEE Trans. Evol. Comput. 19(5), 694–716 (2015). [MOEA/DD]CrossRef
7.
Yuan, Y., Xu, H., Wang, B., Yao, X.: A new dominance relation-based evolutionary algorithm for many-objective optimization. IEEE Trans. Evol. Comput. 20(1), 16–37 (2016). [Theta-DEA]CrossRef
8.
Xiang, Y., Zhou, Y., Li, M.: Chen. Z.: A vector angle-based evolutionary algorithm for unconstrained many-objective optimization. IEEE Trans. Evol. Comput. 21(1), 131–152 (2017). [VaEA]CrossRef
9.
Asafuddoula, M., Ray, T., Sarker, R.: A decomposition-based evolutionary algorithm for many objective optimization. IEEE Trans. Evol. Comput. 19(3), 445–460 (2015). [I-DBEA]CrossRef
10.
He, Z., Yen, G.: Many-objective evolutionary algorithms based on coordinated selection strategy. IEEE Trans. Evol. Comput. 21(2), 220–233 (2017). [MaOEA-CSS]CrossRef
11.
Yuan, Y., Xu, H., Wang, B., Zhang, B., Yao, X.: Balancing convergence and diversity in decomposition-based many-objective optimizers. IEEE Trans. Evol. Comput. 20(2), 180–198 (2016). [MOEA/D-DU]CrossRef
12.
Das, I., Dennis, J.: Normal-boundary intersection: A new method for generating the Pareto surface in nonlinear multicriteria optimization problems. SIAM J. Optim. 8(3), 631–647 (1998)CrossRefMATHMathSciNet
13.
Ishibuchi, H., Setoguchi, Y., Masuda, H., Nojima, Y.: Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes. IEEE Trans. Evol. Comput. 21(2), 169–190 (2017)CrossRef
14.
Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable test problems for evolutionary multiobjective optimization. In: International Conference on Evolutionary Multi-Criterion Optimization, pp. 105–145. Springer (2005). [DTLZ]
Metadata
Title
A Many-Objective Evolutionary Algorithm with Reference Point-Based and Vector Angle-Based Selection
Authors
Chen-Yu Lee
Jia-Fong Yeh
Tsung-Che Chiang
Copyright Year
2018
Publisher
Springer Singapore
Book
Genetic and Evolutionary Computing

Print ISBN: 978-981-10-6486-9

Electronic ISBN: 978-981-10-6487-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-6487-6_1

Premium Partner

    Image Credits