Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study

Peng，Yiming; Ishibuchi，Hisao

10.1007/978-3-031-14721-0_10

2022

17th International Conference on Parallel Problem Solving from Nature (PPSN)

0302-9743

1611-3349

978-3-031-14720-3

LECT NOTES ARTIF INT

13399 LNCS

138-150

SEP 10-14, 2022

null,Dortmund,GERMANY

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

SPRINGER INTERNATIONAL PUBLISHING AG

Many real-world multi-modal multi-objective optimization problems are subject to continuously changing environments, which requires the optimizer to track multiple equivalent Pareto sets in the decision space. To the best of our knowledge, this type of optimization problems has not been studied in the literature. To fill the research gap in this area, we provide a preliminary study on dynamic multi-modal multi-objective optimization. We give a formal definition of dynamic multi-modal multi-objective optimization problems and point out some key challenges in solving them. To facilitate algorithm development, we suggest a systematic approach to construct benchmark problems. Furthermore, we provide a feature-rich test suite containing 10 novel dynamic multi-modal multi-objective test problems.

Benchmark problems Dynamic multi-objective optimization Evolutionary multi-objective optimization Multi-modal multi-objective optimization

第一 ; 通讯

英语

EI ; CPCI-S

National Natural Science Foundation of China[61876075]

Computer Science

Computer Science, Artificial Intelligence

WOS:000871753400010

20223712707320

Benchmarking

Optimization Techniques:921.5

2-s2.0-85137261296

Scopus

Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation,Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Peng，Yiming,Ishibuchi，Hisao. Dynamic Multi-modal Multi-objective Optimization: A Preliminary Study[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2022:138-150.