Suchergebnisse - Dynamic constrained multi-objective optimization problems

A coevolutionary response framework for dynamic constrained multi-objective optimization problems

Autoren: Bao, Qian Wang, Maocai Yang, Shengxiang et al.

Schlagwörter: Dynamic constrained multi-objective optimization, Cooperative response optimization, Dual population

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/2086/25286; https://doi.org/10.1109/TEVC.2025.3595410

Verfügbarkeit: https://hdl.handle.net/2086/25286
https://doi.org/10.1109/TEVC.2025.3595410

Decision space dynamic niching-based method for constrained multiobjective evolutionary optimization.

Autoren: Yu, Fan Chen, Qun Zhou, Jinlong

Quelle: European Journal of Operational Research. Jan2026, Vol. 328 Issue 2, p574-590. 17p.

Schlagwörter: *PARETO optimum, *MATHEMATICAL optimization, MULTI-objective optimization, CONSTRAINED optimization, HETEROGENEITY, EVOLUTIONARY algorithms

Dynamic Constrained Boundary Method for Constrained Multi-Objective Optimization

Autoren: Qiuzhen Wang Zhibing Liang Juan Zou et al.

Quelle: Mathematics, Vol 10, Iss 23, p 4459 (2022)

Schlagwörter: constrained multi-objective optimization problems (CMOPs), dynamic constrained boundary, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2227-7390/10/23/4459; https://doaj.org/toc/2227-7390

Zugangs-URL: https://doaj.org/article/dc585e0d382a4d55ac49e199d3b1d904

Constrained multi-objective optimization assisted by competitive mechanism based reward auxiliary optimization problems.

Autoren: Zhang, Haoming Dang, Qianlong Feng, Xinyu et al.

Quelle: Swarm & Evolutionary Computation. Aug2025, Vol. 97, pN.PAG-N.PAG. 1p.

Schlagwörter: Multi-objective optimization, Optimization algorithms, Constrained optimization, Evolutionary algorithms, Probability theory

A novel particle swarm optimization algorithm with local search for dynamic constrained multi-objective optimization problems

Autoren: Liping Jia Jingxuan Wei

Quelle: 2013 IEEE Congress on Evolutionary Computation. :2436-2443

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ieeexplore.ieee.org/document/6557861/
http://ieeexplore.ieee.org/document/6557861/
https://dblp.uni-trier.de/db/conf/cec/cec2013.html#WeiJ13

Hyper rectangle search based particle swarm algorithm for dynamic constrained multi-objective optimization problems

Autoren: Jingxuan Wei Yuping Wang

Quelle: 2012 IEEE Congress on Evolutionary Computation. :1-8

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ieeexplore.ieee.org/abstract/document/6256137
https://dblp.uni-trier.de/db/conf/cec/cec2012.html#WeiW12
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000006256137

Immune Optimization Approach for Dynamic Constrained Multi-Objective Multimodal Optimization Problems

Autoren: Min Liao Lei Wang Zhuhong Zhang

Quelle: American Journal of Operations Research. :193-202

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Zugangs-URL: http://www.scirp.org/journal/PaperDownload.aspx?paperID=19935
https://file.scirp.org/Html/6-1040098_19935.htm
https://www.scirp.org/journal/PaperDownload.aspx?DOI=10.4236/ajor.2012.22022
https://file.scirp.org/pdf/AJOR20120200005_69561559.pdf
http://www.scirp.org/journal/doi.aspx?DOI=10.4236/ajor.2012.22022

A prediction and weak coevolution-based dynamic constrained multi-objective optimization

Autoren: Gong, Dunwei Rong, Miao Hu, Na et al.

Schlagwörter: dynamic multi-objective optimization, constraint, prediction, weak coevolution, exploration and exploitation

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/2086/24603; https://doi.org/10.1109/TEVC.2024.3418470

Verfügbarkeit: https://hdl.handle.net/2086/24603
https://doi.org/10.1109/TEVC.2024.3418470

Dynamic constrained multi-objective optimization algorithm based on co-evolution and diversity enhancement

Autoren: Che, Wang Zheng, Jinhua Hu, Yaru et al.

Schlagwörter: Dynamic constrained multiobjective optimization, Evolutionary algorithms, Co-evolution, Change response strategy

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/2086/23991; https://doi.org/10.1016/j.swevo.2024.101639

Verfügbarkeit: https://hdl.handle.net/2086/23991
https://doi.org/10.1016/j.swevo.2024.101639

A multi-task multi-objective evolutionary algorithm for constrained multi-objective optimization problems.

Autoren: Liu, Tianyu Wu, Yu Xu, He

Quelle: Memetic Computing; Sep2025, Vol. 17 Issue 3, p1-29, 29p

Multi-objective optimisation of dynamic short-term credit portfolio selection : the adoption of third party logistics credit for financing working capital constrained small and medium sized enterprises in supply chains

Autoren: Jiao, Feng

Zugangs-URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779783

Dynamic Constrained Boundary Method for Constrained Multi-Objective Optimization.

Autoren: Wang, Qiuzhen Liang, Zhibing Zou, Juan et al.

Quelle: Mathematics (2227-7390); Dec2022, Vol. 10 Issue 23, p4459, 16p

Schlagwörter: CONSTRAINED optimization, EVOLUTIONARY algorithms, MATHEMATICAL optimization, SEARCH algorithms, PROBLEM solving, FORCED migration, ALGORITHMS

A dynamic constrained multi-objective evolutionary algorithm with a dual prediction mechanism.

Autoren: Yang, Zhe Deng, Libao Li, Chunlei et al.

Quelle: Expert Systems with Applications. Feb2026:Part A, Vol. 297, pN.PAG-N.PAG. 1p.

Schlagwörter: *MULTI-objective optimization, *EVOLUTIONARY algorithms, *OPTIMIZERS (Computer software), *STATISTICAL sampling, *DYNAMIC programming, *PREDICTION models

Penalty and prediction methods for dynamic constrained multi-objective optimization

Autoren: Wang, Fengxia Huang, Min Yang, Shengxiang et al.

Schlagwörter: Dynamic constrained multi-objective optimization problems, Penalty function, Inverse Gaussian process model, Test instances

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/2086/23082; https://doi.org/10.1016/j.swevo.2023.101317

Verfügbarkeit: https://hdl.handle.net/2086/23082
https://doi.org/10.1016/j.swevo.2023.101317

A Dynamic Tri-Stage Framework with Neural Network-Assisted Search for Constrained Multi-objective Optimization.

Autoren: Dang, Qianlong Hong, Xinkang Sun, Xianpeng

Quelle: Expert Systems with Applications. Mar2026:Part C, Vol. 298, pN.PAG-N.PAG. 1p.

Schlagwörter: *MULTI-objective optimization, *CONSTRAINED optimization, *ARTIFICIAL neural networks, *SOFTWARE frameworks, *MATHEMATICAL programming, *MATHEMATICAL optimization, *EVOLUTIONARY algorithms

A parallel variable-fidelity algorithm for efficient constrained multi-objective aerodynamic design optimization.

Autoren: Zhang, Yu Wang, Zhenkun Han, Zhong-Hua

Quelle: Physics of Fluids. Aug2024, Vol. 36 Issue 8, p1-14. 14p.

Schlagwörter: *COMPUTATIONAL fluid dynamics, *EVOLUTIONARY algorithms, *PARALLEL algorithms, *GLOBAL optimization, *BUDGET

Decision-Maker's Preference-Driven Dynamic Multi-Objective Optimization.

Autoren: Adekoya, Adekunle Rotimi Helbig, Mardé

Quelle: Algorithms. Nov2023, Vol. 16 Issue 11, p504. 26p.

Schlagwörter: *OPTIMIZATION algorithms, *DIFFERENTIAL evolution, *PERFORMANCE standards, *PROBLEM solving

A dual dynamic constraint boundary based constrained multi-objective evolutionary algorithm for small feasible regions.

Autoren: Zhu, Cong Yang, Yongkuan Kong, Xiangsong et al.

Quelle: Expert Systems with Applications. May2025, Vol. 275, pN.PAG-N.PAG. 1p.

Schlagwörter: *MULTI-objective optimization, *EVOLUTIONARY algorithms, *CONSTRAINT satisfaction, *COEVOLUTION, *ALGORITHMS

Constrained Multi-objective Optimization with Deep Reinforcement Learning Assisted Operator Selection

Autoren: Ming, Fei Gong, Wenyin Wang, Ling et al.

Index Begriffe: Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, text

URL: http://arxiv.org/abs/2402.12381

Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem

Autoren: Pathiranage, Ishara Hewa Neumann, Frank Antipov, Denis et al.

Index Begriffe: Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2404.06014