TY - GEN
T1 - An efficient multi-objective evolutionary algorithm based on minimum spanning tree
AU - Li, Miqing
AU - Zheng, Jinhua
AU - Xiao, Guixia
PY - 2008
Y1 - 2008
N2 - Fitness assignment and external population maintenance are two important parts of multi-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.
AB - Fitness assignment and external population maintenance are two important parts of multi-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.
UR - http://www.scopus.com/inward/record.url?scp=55749114557&partnerID=8YFLogxK
U2 - 10.1109/CEC.2008.4630860
DO - 10.1109/CEC.2008.4630860
M3 - Conference contribution
AN - SCOPUS:55749114557
SN - 9781424418237
T3 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
SP - 617
EP - 624
BT - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
T2 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
Y2 - 1 June 2008 through 6 June 2008
ER -