Title :
Multi-objective evolutionary programming without non-domination sorting is up to twenty times faster
Author :
Qu, B.Y. ; Suganthan, P.N.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Abstract :
In this paper, multi-objective evolutionary programming (MOEP) using fuzzy rank-sum with diversified selection is introduced. The performances of this algorithm as well as MOEP with non-domination sorting on the set of benchmark functions provided for CEC2009 Special Session and competition on Multi-objective Optimization are reported. With this rank-sum sorting and diversified selection, the speed of the algorithm has increased significantly, in particular by about twenty times on five objective problems when compared with the implementation using the non-domination sorting. Beside this, the proposed approach has performed either comparable or better than the MOEP with non-domination sorting.
Keywords :
evolutionary computation; fuzzy set theory; CEC2009 Special Session; diversified selection; fuzzy rank-sum; multiobjective evolutionary programming; Artificial intelligence; Evolutionary computation; Genetic programming; Random number generation; Sorting;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983312