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Mukhopadhyay / Sarkar / Deb Contemporary Advancement in Evolutionary Multi-objective Optimization
Erscheinungsjahr 2026
ISBN: 978-981-957908-2
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 234 Seiten
Reihe: Genetic and Evolutionary Computation
ISBN: 978-981-957908-2
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
This endeavour presents a rich collection of contemporary advances in evolutionary multi-objective optimisation algorithms, blending foundational concepts with state-of-the-art research and real-world applications. Featuring contributions from leading experts, it offers clear insights into modern EMO methodologies, emerging AI-EC integrations, and diverse problem-solving domains. An essential reference for researchers, practitioners, and students exploring intelligent optimisation Algorithms.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
"Balancing exploration-exploitation using Switching Mechanism Integrated with Adaptive Heterogeneous Comprehensive Learning PSO and L-SHADEBalancing exploration-exploitation using Switching Mechanism Integrated with Adaptive Heterogeneous Comprehensive Learning PSO and L-SHADE".- "Evolutionary Multi- and Many-objective Optimization: Enhancements using Machine Learning".- "A Many-Objective Optimized Folded Cross Regression Model (FCRM) with Unspecified Targets: A Critical Analysis".- "Emerging Techniques for Evolutionary Single- and Multi-Objective Optimization with Application to Humanoid Robot Gait Generation".- "Optimization models in Nurse Scheduling – A Review of last five years".- "A Review of Bilevel Optimization Methods, Emerging Applications, and Recent Advancements".- "A Review of Advances in Multi-Objective Optimization for Facility Location Problems".- "A Survey on Recent Advances in Multiobjective Evolutionary Clustering".




