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Einband grossMetaheuristics for Resource Deployment under Uncertainty in Complex Systems
ISBN/GTIN

Metaheuristics for Resource Deployment under Uncertainty in Complex Systems

E-BookPDF0 - No protectionE-Book
210 Seiten
Englisch
Taylor & Franciserschienen am30.09.20211. Auflage
This book analyzes how to set locations for the deployment of resources to incur the best performance at the lowest cost. Resources can be static nodes and moving nodes while services for a specific area or for customers can be provided.mehr
Verfügbare Formate
BuchGebunden
EUR118,50
TaschenbuchKartoniert, Paperback
EUR63,00
E-BookPDF0 - No protectionE-Book
EUR62,49
E-BookEPUB0 - No protectionE-Book
EUR62,49

Produkt

KlappentextThis book analyzes how to set locations for the deployment of resources to incur the best performance at the lowest cost. Resources can be static nodes and moving nodes while services for a specific area or for customers can be provided.
Details
Weitere ISBN/GTIN9781000432886
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis0 - No protection
Erscheinungsjahr2021
Erscheinungsdatum30.09.2021
Auflage1. Auflage
Seiten210 Seiten
SpracheEnglisch
Dateigrösse6512 Kbytes
Illustrationen44 schwarz-weiße Abbildungen, 2 schwarz-weiße Fotos, 42 schwarz-weiße Zeichnungen, 38 schwarz-weiße Tabellen
Artikel-Nr.5663641
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
1. Introduction
2. Stochastic Node Deployment for Area Coverage Problem
3. Stochastic Dynamic Node Deployment for Target Coverage Problem
4. Robust Node Deployment for Cooperative Coverage Problem
5. Fuzzy Node Deployment for Cooperative Coverage Problem
6. Simulation-based Evaluation Analysis of Node Deployment under Risk Preference
7. Overview and Future Directionsmehr

Autor

Shuxin Ding is currently an assistant researcher with the Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited. His current research interests include railway scheduling, evolutionary computation, multi-objective optimization, and optimization under uncertainty.

Chen Chen is currently a professor with the School of Automation, Beijing Institute of Technology. Her current research interests include complicated systems, multi-objective optimization, and distributed simulation.

Qi Zhang is currently a chief researcher of China Academy of Railway Sciences Corporation Limited, and a leader in railway technical expertise. His research interests include railway signal and communication, automatic train operation, train operation control, intelligent dispatching, and cooperative control of multiple trains.

Bin Xin is currently a professor with the School of Automation, Beijing Institute of Technology. His current research interests include search and optimization, evolutionary computation, unmanned systems, and multi-agent systems.

Panos M. Pardalos is a Distinguished Professor in the Department of Industrial and Systems Engineering at the University of Florida, and an affiliated faculty of the Biomedical Engineering and Computer Science & Information & Engineering departments. He has published over 500 journal papers and edited/authored over 200 books. He is one of the most cited authors and has graduated 65 Ph.D. students so far.
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Ding, Shuxin