Benchmarks and Hybrid Algorithms in Optimization and Applications [electronic resource] / edited by Xin-She Yang.

Colaborador(es): Yang, Xin-She [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Springer Tracts in Nature-Inspired ComputingEditor: Singapore : Springer Nature Singapore : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: VIII, 246 p. 147 illus., 116 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819939701Tema(s): Computational intelligence | Mathematical optimization | Artificial intelligence | Computational Intelligence | Optimization | Artificial IntelligenceFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
1. Nature-Inspired Algorithms: Overview and Open Problems -- 2. Hybrid algorithms: Components, Hybridization and Examples -- 3. Role of Benchmarks in Optimization -- 4. Travelling Salesman Problems: Symmetric and Asymmetric Cases -- 5. Scheduling Problems: Benchmarks and Implementation -- 6. Active Learning Solution for Semantic Labelling of Earth Observation Satellite Images -- 7. Development of an Ensemble Modelling Framework for Data Analytics in Supply Chain Management -- 8. An Application of Data Mining to Build the OD Matrix in Developing Countries: An Argentinean Case Study -- 9. Deep Learning-based Efficient Customer Segmentation for Online Retail Business -- 10. Application of a Routing Model with a Time Limit for the Collection of RSU in an Argentinian City -- 11. Network Weakness Detection: Case Studies -- 12. Unknown Target Searching by Swarm Robots: A Case Study.
En: Springer Nature eBookResumen: This book is specially focused on the latest developments and findings on hybrid algorithms and benchmarks in optimization and their applications in sciences, engineering, and industries. The book also provides some comprehensive reviews and surveys on implementations and coding aspects of benchmarks. The book is useful for Ph.D. students and researchers with a wide experience in the subject areas and also good reference for practitioners from academia and industrial applications.
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1. Nature-Inspired Algorithms: Overview and Open Problems -- 2. Hybrid algorithms: Components, Hybridization and Examples -- 3. Role of Benchmarks in Optimization -- 4. Travelling Salesman Problems: Symmetric and Asymmetric Cases -- 5. Scheduling Problems: Benchmarks and Implementation -- 6. Active Learning Solution for Semantic Labelling of Earth Observation Satellite Images -- 7. Development of an Ensemble Modelling Framework for Data Analytics in Supply Chain Management -- 8. An Application of Data Mining to Build the OD Matrix in Developing Countries: An Argentinean Case Study -- 9. Deep Learning-based Efficient Customer Segmentation for Online Retail Business -- 10. Application of a Routing Model with a Time Limit for the Collection of RSU in an Argentinian City -- 11. Network Weakness Detection: Case Studies -- 12. Unknown Target Searching by Swarm Robots: A Case Study.

This book is specially focused on the latest developments and findings on hybrid algorithms and benchmarks in optimization and their applications in sciences, engineering, and industries. The book also provides some comprehensive reviews and surveys on implementations and coding aspects of benchmarks. The book is useful for Ph.D. students and researchers with a wide experience in the subject areas and also good reference for practitioners from academia and industrial applications.

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