Proposal of a realistic many-objective test suite

Chen，Weiyu; Ishibuchi，Hisao; Shang，Ke

10.1007/978-3-030-58112-1_14

2020

0302-9743

1611-3349

LECT NOTES ARTIF INT

12269 LNCS

201-214

Real-world many-objective optimization problems are not always available as easy-to-use test problems. For example, their true Pareto fronts are usually unknown, and they are not scalable with respect to the number of objectives or decision variables. Thus, the performance of existing multi-objective evolutionary algorithms is always evaluated using artificial test problems. However, there exist some differences between frequently-used many-objective test problems and real-world problems. In this paper, first we clearly point out one difference with respect to the effect of changing the value of each decision variable on the location of the objective vector in the objective space. Next, to make artificial test problems more realistic, we introduce a coefficient matrix to their problem structure. Then, we demonstrate that a different coefficient matrix leads to a different difficulty of a test problem. Finally, based on these observations, we propose a realistic many-objective test suite using various coefficient matrices.

Coefficient matrix Many-objective optimization Many-objective test suite Multi-objective evolutionary algorithm

第一 ; 通讯

英语

EI

20203909228637

Vector spaces ; Testing ; Evolutionary algorithms ; Matrix algebra

Management:912.2 ; Mathematics:921 ; Algebra:921.1

2-s2.0-85091281067

Scopus

Shenzhen Key Laboratory of Computational Intelligence,University Key Laboratory of Evolving Intelligent Systems of Guangdong Province,Department of Computer Science and Engineering,Southern University of Science and Technology (SUSTech),Shenzhen,China

Chen，Weiyu,Ishibuchi，Hisao,Shang，Ke. Proposal of a realistic many-objective test suite[C],2020:201-214.