Based Cost Differential Evolution Algorithm for Multi-objective Optimization Problems

Authors

  • Chiha Ibtissem
  • Liouane Hend ENIM Monastir, TUNISIA

Keywords:

Differential Evolution, global numerical optimization, multi-objective optimisation

Abstract

In this paper, we present A new variant of the Differential Evolution algorithm. Our proposed algorithm called Based cost Differential Evolution (Bc-DE), generated the mutant vector by adding a weighted difference of two cost function multiplied by a vector selected randomly to the best individual vector. The performance of the Bc-DE algorithm is broadly evaluated on several bound-constrained nonlinear and non-differentiable continuous numerical optimization problems and compares with the conventional DE and several others DE variants. It is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods.

Author Biography

Liouane Hend, ENIM Monastir, TUNISIA

Electical Ing. Departement

References

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Published

2017-10-26

How to Cite

Ibtissem, C., & Hend, L. (2017). Based Cost Differential Evolution Algorithm for Multi-objective Optimization Problems. Asian Journal of Applied Sciences, 5(5). Retrieved from https://ajouronline.com/index.php/AJAS/article/view/1624

Issue

Vol. 5 No. 5 (2017): October 2017

Section

Articles

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