Lecture notes in computer science, Год журнала: 2024, Номер unknown, С. 137 - 153
Опубликована: Янв. 1, 2024
Язык: Английский
Swarm and Evolutionary Computation, Год журнала: 2025, Номер 94, С. 101894 - 101894
Опубликована: Фев. 28, 2025
Язык: Английский
Процитировано
0
Mathematics, Год журнала: 2025, Номер 13(9), С. 1441 - 1441
Опубликована: Апрель 28, 2025
When addressing constrained multi-objective optimization problems (CMOPs), the key challenge lies in achieving a balance between objective functions and constraint conditions. However, existing evolutionary algorithms exhibit certain limitations when tackling CMOPs with complex feasible regions. To address this issue, paper proposes algorithm based on dual-population cooperative correlation (CMOEA-DCC). Under CMOEA-DDC framework, system maintains two independently evolving populations: driving population conventional population. These populations share information through collaborative interaction mechanism, where focuses optimization, while balances both objectives constraints. further enhance performance of algorithm, shift-based density estimation (SDE) method is introduced to maintain diversity solutions population, multi-criteria evaluation metric adopted improve feasibility quality normal was compared seven representative (CMOEAs) across various test real-world application scenarios. Through an in-depth analysis series experimental results, it can be concluded that significantly outperforms other competing terms performance.
Язык: Английский
Процитировано
0
2022 IEEE Congress on Evolutionary Computation (CEC), Год журнала: 2024, Номер unknown, С. 1 - 8
Опубликована: Июнь 30, 2024
Язык: Английский
Процитировано
0
Lecture notes in computer science, Год журнала: 2024, Номер unknown, С. 137 - 153
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0