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An efficient mufti-objective evolutionary algorithm based on Minimum Spanning Tree

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3 Author(s)
Miqing Li ; Inst. of Inf. Eng., Xiangtan Univ., Xiangtan ; Jinhua Zheng ; Guixia Xiao

Fitness assignment and external population maintenance are two important parts of mufti-objective evolutionary algorithms. In this paper, we propose a new MOEA which uses the information of minimum spanning tree to assign fitness and maintain the external population. Moreover, a Minimum Spanning Tree Crowding Distance (MSTCD) is defined to estimate the density of solutions. From an extensive comparative study with three other MOEAs on a number of two and three objective test problems, it is observed that the proposed algorithm has good performance in convergence and distribution.

Published in:
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Date of Conference: 1-6 June 2008

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