吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (06): 1658-1665.doi: 10.7964/jdxbgxb201306036

• paper • Previous Articles     Next Articles

High dimension multi-objective visualization based on single objective fitting

BI Xiao-jun, LI Bo   

  1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
  • Received:2012-07-22 Online:2013-11-01 Published:2013-11-01

RICH HTML

0   

PDF (PC)

407

Abstract:

Current visualization techniques failed to effectively display the high dimension multi-objective optimization problems. To overcome this disadvantage, a new sub-diagram visualization technology based on single objective fitting is proposed. The new visualization technology displays the Pareto solution set in sub-diagram form whose number is the same as objectives. Additionally, the Pareto approximate set is drawn by the fitting location in the sub-diagram. The proposed method displays effectively the convergence and distribution of the Pareto approximate set;meanwhile, the relative merits of the performance on a single solution in each dimension objective and the comparison of the performance of different solutions in the same objective are displayed effectively. Numerical experiments show that the new visualization technique plays a key role in helping decision-makers carry on analysis and decision for multi-objective optimization problems.

Key words: computer application, visualization technology of high dimension multi-objective, sub-diagram visualization technology, single objective fitting, the Pareto front

CLC Number: 

  • TP391

[1] Ortiz M C,Sarabia L A. Improving the visualization of the Pareto-optimal front for the multi-response optimization of chromatographic determinations[J]. Analytica Chimica Acta, 2011,687(2):129-136.

[2] Claessen J H T,Van W,Jarke J. Flexible linked axes for multivariate data visualization[J]. IEEE Transactions on Visualization and Computer Graphics, 2011,17(12):2310-2316.

[3] Stump G,Lego S,Yukish M. Visual steering commands for trade space exploration: User-guided sampling with example[J]. Journal of Computing and Information Science in Engineering, 2009,9(4):1-10.

[4] Zou Xiu-fen,Chen Yu,Liu Min-zhong. A new evolutionary algorithm for solving many-objective optimization problems[J].IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics,2008,38(5):1402-1412.

[5] Efremov R,Insua D R,Lotov A. A framework for participatory decision support using Pareto frontier visualization, goal identification and arbitration[J]. European Journal of Operational Research, 2009,199(2):459-467.

[6] Agrawal G, Bloebaum C L,Lewis K. Intuitive design selection using visualized n-dimensional pareto frontier[C]//46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics & Materials Conference,Austin, T X, USA,2005: 1813-1826.

[7] Taghavi T,Pimentel A D,Sabeghi M. VMODEX: A novel visualization tool for rapid analysis of heuristic-based multi-objective design space exploration of heterogeneous MPSoC architectures[J]. Simulation Modelling Practice and Theory,2012,22(5):166-196.

[8] Po-Wen C,Christina L B. Hyper-radial visualization (HRV) method with range-based preferences for multi-objective decision making[J]. Struct Multidisc Optim,2010 40(1):97-115.

[9] Bernataviiené J,Dzemyda Gintautas,Kurasova O. Optimal decisions in combining the SOM with nonlinear projection methods[J]. European Journal of Operational Research, 2006,173(3):729-745.

[10] Masafumi Y,Tomohiro Y,Takeshi F. Study on effect of MOGA with interactive island model using visualization[C]//2010 IEEE Congress on Evolutionary Computation (CEC), Barcelona,Spain,2010:1-6.

[11] Ivosev G,Burton L,Bonner R. Dimensionality reduction and visualization in principal component analysis[J]. Analytical Chemistry, 2008, 80 (13):4933-4944.

[12] Deb K, Thiele L, Laumanns M. Scalable multi-objective optimization test problems[C]//Proceedings of the 2002 Congress on Evolutionary Computation,Honolulu,H I,2002: 825-830.

[13] Problems included in jMetal[DB/OL].[201-04-27].http:[C]//jmetal.sourceforge.net/problems.html.

[14] Pham M T, Zhang D, Koh, C S. Multi-guider and cross-searching approach in multi-objective particle swarm optimization for electromagnetic problems[J]. IEEE Transactions on Magnetics, 2012,48(2):539-542.

[15] Zitzler E, Thiele L. Multi-objective evolutionary algorithms: A comparative case study and the strength Pareto approach[J]. IEEE Transactions on Evolutionary Computations, 1999, 6(2):182-197.
[1] LIU Fu,ZONG Yu-xuan,KANG Bing,ZHANG Yi-meng,LIN Cai-xia,ZHAO Hong-wei. Dorsal hand vein recognition system based on optimized texture features [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1844-1850.
[2] WANG Li-min,LIU Yang,SUN Ming-hui,LI Mei-hui. Ensemble of unrestricted K-dependence Bayesian classifiers based on Markov blanket [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1851-1858.
[3] JIN Shun-fu,WANG Bao-shuai,HAO Shan-shan,JIA Xiao-guang,HUO Zhan-qiang. Synchronous sleeping based energy saving strategy of reservation virtual machines in cloud data centers and its performance research [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1859-1866.
[4] ZHAO Dong,SUN Ming-yu,ZHU Jin-long,YU Fan-hua,LIU Guang-jie,CHEN Hui-ling. Improved moth-flame optimization method based on combination of particle swarm optimization and simplex method [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1867-1872.
[5] LIU En-ze,WU Wen-fu. Agricultural surface multiple feature decision fusion disease judgment algorithm based on machine vision [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1873-1878.
[6] OUYANG Dan-tong, FAN Qi. Clause-level context-aware open information extraction [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1563-1570.
[7] LIU Fu, LAN Xu-teng, HOU Tao, KANG Bing, LIU Yun, LIN Cai-xia. Metagenomic clustering method based on k-mer frequency optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1593-1599.
[8] GUI Chun, HUANG Wang-xing. Network clustering method based on improved label propagation algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1600-1605.
[9] LIU Yuan-ning, LIU Shuai, ZHU Xiao-dong, CHEN Yi-hao, ZHENG Shao-ge, SHEN Chun-zhuang. LOG operator and adaptive optimization Gabor filtering for iris recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1606-1613.
[10] CHE Xiang-jiu, WANG Li, GUO Xiao-xin. Improved boundary detection based on multi-scale cues fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1621-1628.
[11] ZHAO Hong-wei, LIU Yu-qi, DONG Li-yan, WANG Yu, LIU Pei. Dynamic route optimization algorithm based on hybrid in ITS [J]. 吉林大学学报(工学版), 2018, 48(4): 1214-1223.
[12] HUANG Hui, FENG Xi-an, WEI Yan, XU Chi, CHEN Hui-ling. An intelligent system based on enhanced kernel extreme learning machine for choosing the second major [J]. 吉林大学学报(工学版), 2018, 48(4): 1224-1230.
[13] FU Wen-bo, ZHANG Jie, CHEN Yong-le. Network topology discovery algorithm against routing spoofing attack in Internet of things [J]. 吉林大学学报(工学版), 2018, 48(4): 1231-1236.
[14] CAO Jie, SU Zhe, LI Xiao-xu. Image annotation method based on Corr-LDA model [J]. 吉林大学学报(工学版), 2018, 48(4): 1237-1243.
[15] HOU Yong-hong, WANG Li-wei, XING Jia-ming. HTTP-based dynamic adaptive streaming video transmission algorithm [J]. 吉林大学学报(工学版), 2018, 48(4): 1244-1253.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd