Contemporary Advancement in Evolutionary Multi-Objective Optimization
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| Autore: |
Mukhopadhyay Somnath
|
| Titolo: |
Contemporary Advancement in Evolutionary Multi-Objective Optimization
|
| Pubblicazione: | Singapore : , : Springer, , 2026 |
| ©2026 | |
| Edizione: | 1st ed. |
| Descrizione fisica: | 1 online resource (318 pages) |
| Disciplina: | 006.3823 |
| Altri autori: |
Mukhopadhyay
|
| Nota di contenuto: | Genetic and Evolutionary Computation -- Contemporary Advancement in Evolutionary Multi-objective Optimization -- Contents -- Balancing 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 Multi-objective Evolutionary Clustering. |
| Sommario/riassunto: | 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. |
| Titolo autorizzato: | Contemporary Advancement in Evolutionary Multi-Objective Optimization |
| ISBN: | 9789819579082 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9911119153103321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Genetic and Evolutionary Computation Series