期刊论文

Jiang, Shouyong

英文

Information Sciences

0020-0255

2020

515

365-387

10.1016/j.ins.2019.12.011

Acknowledgment SJ, MK, and NK acknowledge the Engineering and Physical Sciences Research Council (EPSRC) for funding project “Synthetic Portabolomics: Leading the way at the crossroads of the Digital and the Bio Economies (EP/N031962/1)”.

本校为其他机构

Population-based evolutionary algorithms have great potential to handle multiobjective optimisation problems. However, the performance of these algorithms depends largely on problem characteristics. There is a need to improve these algorithms for wide applicability. References, often specified by the decision maker's preference in different forms, are very effective to boost the performance of algorithms. This paper proposes a novel framework for effective use of references to strengthen algorithms. This framework considers references as search...