logo

SCIENCE CHINA Information Sciences, Volume 62, Issue 7: 070212(2019) https://doi.org/10.1007/s11432-018-9729-5

A pigeon-inspired optimization algorithm for many-objective optimization problems

More info
  • ReceivedAug 13, 2018
  • AcceptedNov 30, 2018
  • PublishedFeb 26, 2019

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. 61806138, U1636220, 61663028, 61702040), Natural Science Foundation of Shanxi Province (Grant No. 201801D121127), Scientific and Technological Innovation Team of Shanxi Province (Grant No. 201805D131007), Ph.D. Research Startup Foundation of Taiyuan University of Science and Technology (Grant No. 20182002), and Beijing Natural Science Foundation (Grant No. 4174089).


Supplement

Appendix A.


References

[1] Duan H, Qiao P. Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. Int Jnl Intel Comp Cyber, 2014, 7: 24-37 CrossRef Google Scholar

[2] Qiu H X, Duan H B. Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design. Sci China Technol Sci, 2015, 58: 1915-1923 CrossRef Google Scholar

[3] Lin Q, Liu S, Zhu Q. Particle Swarm Optimization With a Balanceable Fitness Estimation for Many-Objective Optimization Problems. IEEE Trans Evol Computat, 2018, 22: 32-46 CrossRef Google Scholar

[4] Deb K, Jain H. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints. IEEE Trans Evol Computat, 2014, 18: 577-601 CrossRef Google Scholar

[5] Yang S, Li M, Liu X. A Grid-Based Evolutionary Algorithm for Many-Objective Optimization. IEEE Trans Evol Computat, 2013, 17: 721-736 CrossRef Google Scholar

[6] Bader J, Zitzler E. HypE: an algorithm for fast hypervolume-based many-objective optimization.. Evolary Computation, 2011, 19: 45-76 CrossRef PubMed Google Scholar

[7] Zhang X, Tian Y, Jin Y. A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization. IEEE Trans Evol Computat, 2015, 19: 761-776 CrossRef Google Scholar

[8] Zhang Q F, Li H. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition. IEEE Trans Evol Computat, 2007, 11: 712-731 CrossRef Google Scholar

  • Figure 1

    Pareto front obtained by different algorithms on the eight-objective DTLZ2 instance. (a) NSGAIII on DTLZ2; (b) GrEA on DTLZ2; (c) HypE on DTLZ2; (d) KnEA on DTLZ2; (e) MOEAD on DTLZ2; (f) MaPIO on DTLZ2.

Copyright 2019 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备18024590号-1