Suchergebnisse - "dynamic multi-objective evolutionary algorithms"

Dynamic Multi-Objective Evolutionary Algorithms: An Overview

Autoren: Elaine Guerrero-Peña Aluízio Araújo Cícero Garrozi

Quelle: Learning and Nonlinear Models. 21:55-82

Dynamic multi-objective evolutionary algorithms in noisy environments

Autoren: Shaaban Sahmoud Haluk Rahmi Topcuoglu Sahmoud S., TOPCUOĞLU H. R.

Weitere Verfasser: Shaaban Sahmoud Haluk Rahmi Topcuoglu Sahmoud S., TOPCUOĞLU H. R.

Quelle: Information Sciences. 634:650-664

Schlagwörter: Social Sciences and Humanities, Information Systems and Management, Social Sciences (SOC), Sosyal Bilimler ve Beşeri Bilimler, Yazılım, Mühendislik, COMPUTER SCIENCE, THEORY & METHODS, ENGINEERING, Biyoenformatik, 02 engineering and technology, BİLGİSAYAR BİLİMİ, TEORİ VE YÖNTEM, Information Systems, Communication and Control Engineering, Sociology, Yapay Zeka, 0202 electrical engineering, electronic engineering, information engineering, COMPUTER SCIENCE, SOFTWARE ENGINEERING, Bilgisayar Bilimi Uygulamaları, Veritabanı ve Veri Yapıları, Computer Sciences, Uncertainty, bioinformatics, BİLGİ BİLİMİ VE KÜTÜPHANE BİLİMİ, Computer Science Applications, Dynamic multi-objective optimization problems, OTOMASYON & KONTROL SİSTEMLERİ, Physical Sciences, Engineering and Technology, Sosyal Bilimler (SOC), Bilgisayar Bilimi, Change detection, Teorik Bilgisayar Bilimi, Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği, Control and System Engineering, BİLGİSAYAR BİLİMİ, YAZILIM MÜHENDİSLİĞİ, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, SOCIAL SCIENCES, GENERAL, AUTOMATION & CONTROL SYSTEMS, algorithms, Bilgi Sistemleri ve Yönetimi, Theoretical Computer Science, BİLGİSAYAR BİLİMİ, YAPAY ZEKA, Database and Data Structures, Artificial Intelligence, Library Sciences, INFORMATION SCIENCE & LIBRARY SCIENCE, Sosyal ve Beşeri Bilimler, Bilgisayar Bilimleri, Social Sciences & Humanities, Engineering, Computing & Technology (ENG), Sosyoloji, Noise detection, Mühendislik, Bilişim ve Teknoloji (ENG), Sosyal Bilimler Genel, COMPUTER SCIENCE, Fizik Bilimleri, Control and Systems Engineering, Mühendislik ve Teknoloji, Kütüphanecilik, Algoritmalar, Kontrol ve Sistem Mühendisliği, Software, Noisy optimization problems

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85151471779&origin=inward
https://hdl.handle.net/11424/288790

Solving the rotating seru production problem with dynamic multi-objective evolutionary algorithms

Autoren: Yong Yin Kan Fang Feng Liu et al.

Quelle: Journal of Management Science and Engineering, Vol 7, Iss 1, Pp 48-66 (2022)

Schlagwörter: Industrial engineering. Management engineering, 9. Industry and infrastructure, Dynamic multi-objective optimization, Assembly, 8. Economic growth, Cellular manufacturing, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, T55.4-60.8, Evolutionary algorithms, Rotating seru

Zugangs-URL: https://doaj.org/article/0aa408907ea747b5894080f749e38327
https://www.sciencedirect.com/science/article/pii/S2096232021000305

A general framework based on dynamic multi-objective evolutionary algorithms for handling feature drifts on data streams

Autoren: Haluk Rahmi Topcuoglu Shaaban Sahmoud

Quelle: Future Generation Computer Systems. 102:42-52

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

Zugangs-URL: https://dblp.uni-trier.de/db/journals/fgcs/fgcs102.html#SahmoudT20
https://doi.org/10.1016/j.future.2019.07.069
https://www.sciencedirect.com/science/article/pii/S0167739X19301748

Dynamic multi-objective evolutionary algorithms for single-objective optimization

Autoren: Ruwang Jiao Sanyou Zeng Jawdat S. Alkasassbeh et al.

Quelle: Applied Soft Computing. 61:793-805

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

Zugangs-URL: https://dblp.uni-trier.de/db/journals/asc/asc61.html#JiaoZAL17
https://www.sciencedirect.com/science/article/pii/S1568494617305124

Exploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms

Autoren: Shaaban Sahmoud Haluk Rahmi Topcuoglu

Quelle: Applied Soft Computing. 85:105783

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

Zugangs-URL: https://www.sciencedirect.com/science/article/pii/S1568494619305642#!
https://www.sciencedirect.com/science/article/pii/S1568494619305642
https://dblp.uni-trier.de/db/journals/asc/asc85.html#SahmoudT19

Dynamic Multi-Objective Evolutionary Algorithms in Noisy Environments

Autoren: Sahmoud, Shaaban Topcuoğlu, Haluk Rahmi FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü

Weitere Verfasser: Sahmoud, Shaaban Topcuoğlu, Haluk Rahmi FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü

Schlagwörter: Change Detection, Dynamic Multi-Objective Optimization Problems, Noise Detection, Noisy Optimization Problems, Uncertainty

Dateibeschreibung: application/pdf

Relation: Information Sciences; Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı; https://hdl.handle.net/11352/4525; 634; 650; 664

Verfügbarkeit: https://hdl.handle.net/11352/4525

Preference integration in progressive dynamic multi-objective evolutionary algorithms

Autoren: Newton, David

Thesis Advisors: Paul Kry (Internal/Supervisor)

Schlagwörter: Computer Science

Relation: Pid: 154773

Verfügbarkeit: https://escholarship.mcgill.ca/concern/theses/nz8062367

Dynamic multi-objective evolutionary algorithms for single-objective optimization.

Autoren: Jiao, Ruwang Zeng, Sanyou Alkasassbeh, Jawdat S. et al.

Quelle: Applied Soft Computing. Dec2017, Vol. 61, p793-805. 13p.

Schlagwörter: Evolutionary algorithms, Mathematical optimization, Artificial neural networks, Problem solving, Machine learning

Solving the rotating seru production problem with dynamic multi-objective evolutionary algorithms.

Autoren: Feng Liu Kan Fang Jiafu Tang et al.

Quelle: Journal of Management Science & Engineering; Mar2022, Vol. 7 Issue 1, p48-66, 19p

Exploiting characterization of dynamism for enhancing dynamic multi-objective evolutionary algorithms.

Autoren: Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Quelle: Applied Soft Computing. Dec2019, Vol. 85, pN.PAG-N.PAG. 1p.

Schlagwörter: Scientific community, Evolutionary algorithms, Evolutionary computation

A key-point-based hybrid prediction dynamic multi-objective evolutionary algorithm.

Autoren: Yang, Yanxiang Yang, Yongkuan

Quelle: Evolutionary Intelligence; Aug2025, Vol. 18 Issue 4, p1-20, 20p

Dynamic multi-objective optimization algorithm based on decomposition and preference

Autoren: Hu, Yaru Zou, Juan Zheng, Jinhua et al.

Schlagwörter: Dynamic multi-objective evolutionary algorithms, Region of interest, Reference points, Changing preference point

Dateibeschreibung: application/pdf

Relation: https://dora.dmu.ac.uk/handle/2086/20858; https://doi.org/10.1016/j.ins.2021.04.055

Verfügbarkeit: https://dora.dmu.ac.uk/handle/2086/20858
https://doi.org/10.1016/j.ins.2021.04.055

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Weitere Verfasser: Sahmoud, Shaaban Topcuoglu, Haluk Rahmi

Schlagwörter: dynamic multi-objective evolutionary algorithms, learning in non-stationary environments, severity of changes, feature drift, memory-based algorithms, FEATURE-SELECTION, OPTIMIZATION

Relation: 2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC); IEEE Congress on Evolutionary Computation; https://hdl.handle.net/11424/226409; WOS:000703998201116

Verfügbarkeit: https://hdl.handle.net/11424/226409

Memory-Assisted Dynamic Multi-Objective Evolutionary Algorithm for Feature Drift Problem

Weitere Verfasser: Sahmoud S., Topcuoglu H.R.

Schlagwörter: dynamic multi-objective evolutionary algorithms, feature drift, learning in non-stationary environments, memory-based algorithms, severity of changes

Relation: 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings; https://hdl.handle.net/11424/248120

Verfügbarkeit: https://hdl.handle.net/11424/248120
https://doi.org/10.1109/CEC48606.2020.9185730

Dynamic Multi-Objective Workflow Scheduling for Cloud Computing Based on Evolutionary Algorithms

Weitere Verfasser: Sill, A Spillner, J Ismayilov, Goshgar et al.

Schlagwörter: Workflow scheduling, resource failures, dynamic multi-objective evolutionary algorithms, OPTIMIZATION

Relation: 2018 IEEE/ACM INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING COMPANION (UCC COMPANION); International Conference on Utility and Cloud Computing; https://hdl.handle.net/11424/226081; WOS:000458720100025

Verfügbarkeit: https://hdl.handle.net/11424/226081
https://doi.org/10.1109/UCC-Companion.2018.00042

A Type Detection Based Dynamic Multi-objective Evolutionary Algorithm

Autoren: TOPCUOĞLU, HALUK RAHMİ Sim, K Kaufmann, P et al.

Weitere Verfasser: TOPCUOĞLU, HALUK RAHMİ Sim, K Kaufmann, P et al.

Schlagwörter: Dynamic Multi-objective Optimization Problems, Non-dominated Sorting Genetic Algorithm (NSGA-II), Type detection, Dynamic Multi-objective Evolutionary Algorithms, NSGA-II, OPTIMIZATION

Relation: APPLICATIONS OF EVOLUTIONARY COMPUTATION, EVOAPPLICATIONS 2018; Lecture Notes in Computer Science; https://hdl.handle.net/11424/226045; WOS:000433244800058

Verfügbarkeit: https://hdl.handle.net/11424/226045
https://doi.org/10.1007/978-3-319-77538-8_58

Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing

Autoren: TOPCUOĞLU, HALUK RAHMİ Ismayilov, Goshgar Topcuoglu, Haluk Rahmi

Weitere Verfasser: TOPCUOĞLU, HALUK RAHMİ Ismayilov, Goshgar Topcuoglu, Haluk Rahmi

Schlagwörter: Workflow scheduling, Resource failures, Changing number of objectives, Dynamic multi-objective evolutionary algorithms, Neural networks, OPTIMIZATION, COST

Relation: FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE; https://hdl.handle.net/11424/235945; WOS:000501936300025

Verfügbarkeit: https://hdl.handle.net/11424/235945
https://doi.org/10.1016/j.future.2019.08.012

A Discriminative Prediction Strategy Based on Multi-View Knowledge Transfer for Dynamic Multi-Objective Optimization.

Autoren: Xu, Hua Zhang, Chenjie Huang, Lingxiang et al.

Quelle: Processes; Mar2025, Vol. 13 Issue 3, p744, 23p

Schlagwörter: MULTI-objective optimization, EVOLUTIONARY algorithms, FORECASTING, ALGORITHMS, KNOWLEDGE transfer

EnsembleFL: A Dynamic Multi-Objective Evolutionary Algorithm based on an Ensemble Feed-forward Prediction.

Autoren: Quanheng Zheng¹ 18839555678@163.com

Quelle: IAENG International Journal of Computer Science. Aug2025, Vol. 52 Issue 8, p2623-2636. 14p.

Schlagwörter: Multi-objective optimization, Evolutionary algorithms, Mathematical optimization, Pragmatism