Handling constrained many-objective optimization problems via problem transformation

Handling constrained many-objective optimization problems via problem transformation

Objectives optimization and constraints satisfaction are two equally important goals to solve constrained many-objective optimization problems (CMaOPs). However, most existing studies for CMaOPs can be classified as feasibility-driven-constrained many-objective evolutionary algorithms (CMaOEAs), and...

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Bibliographic Details
Main Authors: Jiao, Ruwang, Zeng, Sanyou, Li, Changhe, Yang, Shengxiang, Ong, Yew-Soon
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Computer science and engineering
Constrained Optimization
Evolutionary Computation
Online Access:https://hdl.handle.net/10356/159938

Internet

https://hdl.handle.net/10356/159938

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