A Hierarchical Pareto Dominance based Multi-objective Approach for the Optimization of Gene Regulatory Network Models

被引：0
|
作者：
Cai, Xinye [1 ]
Hu, Zhenzhou [1 ]
Das, Sanjoy [2 ]
Welch, Stephen M. [3 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing, Jiangsu, Peoples R China
[2] Kansas State Univ, Dept Elect & Comp Engn, Manhattan, KS USA
[3] Kansas State Univ, Dept Agron, Manhattan, KS USA
来源：
2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2012年
关键词：
SIMPLEX HYBRID APPROACH; REDUCTION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, a hierarchical Pareto dominance based multi-objective evolutionary approach is proposed for the optimization of gene regulatory network models. The approach is presented based on the neglected observations in GRN optimization that (i) structural dependencies exist among objectives; and (ii) some objectives may be more important than others. The hierarchical Pareto dominance is able to reduce the number of objectives during optimization process and increase the selection pressure to relieve the many objective problem. The proposed hierarchical Pareto dominance based multi-objective approach is verified and compared with classical Pareto dominance based algorithm NSGAII on the gene regulatory network optimization problem. The results obtained indicate that the presented approach has great performance when no noise exist. Also it shows superior results compared to NSGAII.
引用
收藏
页数：6
相关论文
共 50 条
  • [31] An improved multi-objective bacterial colony chemotaxis algorithm based on Pareto dominance
    Zhigang Lu
    Shengjing Qi
    Jiangfeng Zhang
    Yao Cai
    Xiaoqiang Guo
    Shifan Luo
    Soft Computing, 2022, 26 : 69 - 87
  • [32] Multi-objective Pareto and GAs nonlinear optimization approach for flyback transformer
    Sobhi Barg
    Kent Bertilsson
    Electrical Engineering, 2019, 101 : 995 - 1006
  • [33] Multi-objective Pareto and GAs nonlinear optimization approach for flyback transformer
    Barg, Sobhi
    Bertilsson, Kent
    ELECTRICAL ENGINEERING, 2019, 101 (03) : 995 - 1006
  • [34] A modified PBI approach for multi-objective optimization with complex Pareto fronts
    Zhang, Qisheng
    Zhu, Wen
    Liao, Bo
    Chen, Xiangtao
    Cai, Lijun
    SWARM AND EVOLUTIONARY COMPUTATION, 2018, 40 : 216 - 237
  • [35] Pareto-MEC for multi-objective optimization
    Sun, CY
    Qi, XH
    Li, O
    2003 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-5, CONFERENCE PROCEEDINGS, 2003, : 321 - 328
  • [36] Local Pareto approximation for multi-objective optimization
    Utyuzhnikov, Sergei
    Maginot, Jeremy
    Guenov, Marin
    ENGINEERING OPTIMIZATION, 2008, 40 (09) : 821 - 847
  • [37] Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits
    Cheng, Ji
    Xue, Bo
    Yi, Jiaxiang
    Zhang, Qingfu
    THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 10, 2024, : 11489 - 11497
  • [38] A novel Pareto-based multi-objective vibration damping optimization algorithm to solve multi-objective optimization problems
    Hajipour, V.
    Mehdizadeh, E.
    Tavakkoli-Moghaddam, R.
    SCIENTIA IRANICA, 2014, 21 (06) : 2368 - 2378
  • [39] A novel Pareto-based multi-objective vibration damping optimization algorithm to solve multi-objective optimization problems
    Hajipour, V. (v.hajipour@basu.ac.ir), 1600, Sharif University of Technology (21):
  • [40] A graph-based algorithm for the multi-objective optimization of gene regulatory networks
    Nghe, Philippe
    Mulder, Bela M.
    Tans, Sander J.
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2018, 270 (02) : 784 - 793
12345