A New Dynamic Population Variation in Genetic Programming

Authors

  • Yanyun Tao School of Urban Rail Transportation, Soochow University, Yangchenghu Campus, Jiexue Rd. No. 8, Xiangcheng Area, Suzhou
  • Minglu Li Computer Science, School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University
  • Jian Cao Computer Science, School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University

Keywords:

Evolutionary algorithm, exponential pivot function, dynamic population variation, instruction matrix, computational effort

Abstract

A dynamic population variation (DPV) in genetic programming (GP) with four innovations is proposed for reducing computational effort and accelerating convergence during the run of GP. Firstly, we give a new stagnation phase definition and the characteristic measure for it. Secondly, we propose an exponential pivot function (EXP) in conjunction with the new stagnation phase definition. Thirdly, we propose an appropriate population variation formula for EXP. Finally, we introduce a scheme using an instruction matrix for producing new individuals to maintain diversity of the population. The efficacy of these innovations in our DPV is examined using four typical benchmark problems. Comparisons among the different characteristic measures have been conducted for regression problems and the proposed measure performed best in all characteristic measures. It is demonstrated that the proposed population variation scheme is superior to fixed and proportionate population variation schemes for sequence induction. It is proved that the new DPV has the capacity to provide solutions at a lower computational effort compared with previously proposed population variation methods and standard genetic programming in most problems.

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Published

2013-03-22

How to Cite

Tao, Y., Li, M., & Cao, J. (2013). A New Dynamic Population Variation in Genetic Programming. COMPUTING AND INFORMATICS, 32(1), 63–87. Retrieved from http://www.cai.sk/ojs/index.php/cai/article/view/1467