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The Journal of Supercomputing

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01-12-2013

Solving symbolic regression problems with uniform design-aided gene expression programming

Authors: Yunliang Chen, Dan Chen, Samee U. Khan, Jianzhong Huang, Changsheng Xie

Published in: The Journal of Supercomputing | Issue 3/2013

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Abstract

Gene Expression Programming (GEP) significantly surpasses traditional evolutionary approaches to solving symbolic regression problems. However, existing GEP algorithms still suffer from premature convergence and slow evolution in anaphase. Aiming at these pitfalls, we designed a novel evolutionary algorithm, namely Uniform Design-Aided Gene Expression Programming (UGEP). UGEP uses (1) a mixed-level uniform table for generating initial population and (2) multiparent crossover operators by taking advantages of the dispersibility of uniform design. In addition to a theoretic analysis, we compared UGEP to existing GEP variants via a number of experiments in dealing with symbolic regression problems including function fitting and chaotic time series prediction. Experimental results indicate that UGEP excels in terms of both the capability of achieving the global optimum and the convergence speed in solving symbolic regression problems.

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Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading MATH

Koza JR (1992) Genetic programming: on the programming of computers by means of natural selection. In: Modeling adaptive multi-agent systems inspired by developmental biology, vol 229

Tsai CC, Huang HC, Chan CK (2011) Parallel elite genetic algorithm and its application to global path planning for autonomous robot navigation. IEEE Trans Ind Electron 10:4813–4821 CrossRef

Chung SH, Chan H (2012) A two-level genetic algorithm to determine production frequencies for economic lot-scheduling problem. IEEE Trans Ind Electron 59:611–619 CrossRef

Zhang X, Hu S, Chen D, Li X (2012) Fast covariance matching with fuzzy genetic algorithm. IEEE Trans Ind Inform 8:148–157 CrossRef

Varadan V, Leung H (2001) Reconstruction of polynomial systems from noisy time-series measurements using genetic programming. IEEE Trans Ind Electron 48:742–748 CrossRef

Ferreira C (2003) Function finding and the creation of numerical constants in gene expression programming. In: Advances in soft computing: engineering design and manufacturing, vol 265

Li X, Zhou C, Xiao W, Nelson PC (2005) Prefix gene expression programming. In: Genetic and evolutionary computation conference (GECCO05), Washington, DC, USA, pp 25–29

Ferreira C (2001) Gene expression programming: a new adaptive algorithm for solving problems. arXiv:cs/0102027

10.

Zuo J, Tang C, Zhang T (2002) Mining predicate association rule by gene expression programming. In: Advances in web-age information management, pp 281–294

11.

Zuo J, Tang C, Li C, Yuan C, Chen A (2004) Time series prediction based on gene expression programming. In: Advances in web-age information management, pp 55–64 CrossRef

12.

Peng J, Tang C, Li C, Hu J-J (2005) M-GEP: a new evolution algorithm based on multi-layer chromosomes gene expression programming. Chin J Comput 28:1459–1466

13.

Zhou C, Xiao W, Tirpak TM, Nelson PC (2003) Evolving accurate and compact classification rules with gene expression programming. IEEE Trans Evol Comput 7:519–531 CrossRef

14.

Karakasis VK, Stafylopatis A (2008) Efficient evolution of accurate classification rules using a combination of gene expression programming and clonal selection. IEEE Trans Evol Comput 12:662–678 CrossRef

15.

Abdelaziz AY, Mekhamer S, Khattab H, Badr M, Panigrahi BK (2012) Gene expression programming algorithm for transient security classification. In: Swarm, evolutionary, and memetic computing. Springer, Berlin, pp 406–416 CrossRef

16.

Wang H, Liu S, Meng F, Li M (2012) Gene expression programming algorithms for optimization of water distribution networks. Proc Eng 37:359–364 CrossRef

17.

Ferreira C (2002) Mutation, transposition, and recombination: an analysis of the evolutionary dynamics. In: The 6th joint conference on information sciences, 4th international work shop on frontiers in evolutionary algorithms

18.

Shi K-F, Dong J-W, Li J-P, Shouning Q, Bo Y (2002) Orthogonal genetic algorithm. Acta Electron Sin 10:1501–1504

19.

Lopes HS, Weinert WR (2004) EGIPSYS: an enhanced gene expression programming approach for symbolic regression problems. Int J Appl Math Comput Sci 14:375–384 MathSciNetMATH

20.

Jiang S, Cai Z, Zuo D (2005) Parallel gene expression programming algorithm based on simulated annealing method. Acta Electron Sin 33:2017–2021

21.

Fang KT, Lin DKJ, Winker P, Zhang Y (2000) Uniform design: theory and application. Technometrics 42:237–248 MathSciNetCrossRefMATH

22.

Wang Y, Fang K (1981) A note on uniform distribution and experimental design. KeXue TongBao 26:485–489 MathSciNetMATH

23.

Hu JJ, Tang CJ, Du L, Zuo J, Peng J (2007) The strategy for diversifying initial population of gene expression programming. Chin J Comput 30:305–310

24.

Koza JR (1994) Genetic programming II: automatic discovery of reusable programs: mitpress

25.

Fang KT, Yang ZH (2000) On uniform design of experiments with restricted mixtures and generation of uniform distribution on some domains. Stat Probab Lett 46:113–120 MathSciNetCrossRefMATH

26.

Xing WX, Xie JX (1999) Advanced computational methods for optimization. Tsinghua University Press, Tsinghua, pp 140–181

27.

Wu S, Zhang Q, Chen H (1997) a new evolutionary algorithm based on family eugenics. J Softw 2

28.

Leung YW, Wang Y (2001) An orthogonal genetic algorithm with quantization for global numerical optimization. IEEE Trans Evol Comput 5:41–53 CrossRef

29.

Huang CM, Lee YJ, Lin DKJ, Huang SY (2007) Model selection for support vector machines via uniform design. Comput Stat Data Anal 52:335–346 MathSciNetCrossRefMATH

30.

Szpiro GG (1997) Forecasting chaotic time series with genetic algorithms. Phys Rev E 55:2557–2568 CrossRef

31.

Cui B, Zhao Z, Tok W (2012) A framework for similarity search of time series cliques with natural relations. IEEE Trans Knowl Data Eng 24:385–398 CrossRef

32.

Khan SU, Bouvry P, Engel T (2012) Energy-efficient high-performance parallel and distributed computing. J Supercomput 60:163–164 CrossRef

33.

Khan SU, Min-Allah N (2012) A goal programming based energy efficient resource allocation in data centers. J Supercomput 61:502–519 CrossRef

Title: Solving symbolic regression problems with uniform design-aided gene expression programming
Authors: Yunliang Chen
Dan Chen
Samee U. Khan
Jianzhong Huang
Changsheng Xie
Publication date: 01-12-2013
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 3/2013
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-013-0943-6

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