Atjaunināt sīkdatņu piekrišanu

Recent Advances in Computational Optimization: Results of the Workshop on Computational Optimization WCO 2019 2021 ed. [Mīkstie vāki]

Edited by
  • Formāts: Paperback / softback, 199 pages, height x width: 235x155 mm, weight: 332 g, 56 Illustrations, color; 34 Illustrations, black and white; X, 199 p. 90 illus., 56 illus. in color., 1 Paperback / softback
  • Sērija : Studies in Computational Intelligence 920
  • Izdošanas datums: 30-Nov-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030588866
  • ISBN-13: 9783030588861
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 91,53 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 107,69 €
  • Ietaupiet 15%
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Formāts: Paperback / softback, 199 pages, height x width: 235x155 mm, weight: 332 g, 56 Illustrations, color; 34 Illustrations, black and white; X, 199 p. 90 illus., 56 illus. in color., 1 Paperback / softback
  • Sērija : Studies in Computational Intelligence 920
  • Izdošanas datums: 30-Nov-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030588866
  • ISBN-13: 9783030588861
Citas grāmatas par šo tēmu:
This book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2019.Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit.

Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.

This book presents recent advances in computational optimization. The book includes important real problems like modeling of physical processes, wildfire and flood risk modeling, workforce planning, parameter settings for controlling different processes, optimal electrical vehicle modeling, bioreactor modeling and design of VLSI.

It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics andother domains can be formulated as optimization problems.
Validation and optimization of dam break ?ood risk mapping based on ?eld test cases in Armenia.- Fire Simulator capable to analyze ?re spread in real time with limited ?eld weather data. Case study - Kresna Fire (2017).- Utilizing Minimum Set-Cover Structures with Several Constraints for Knowledge Discovery on Large Literature Databases.- Evaluation of optimal charging station location for electric vehicles: an Italian case-study.- InterCriteria Analysis of the Evaporation Parameter In?uence on Ant Colony Optimization Algorithm: A Workforce Planning Problem.- Caterpillar Alignment Distance for Rooted Labeled Caterpillars: Distance Based on Alignments Required to Be Caterpillars.- ICrA over Ordered Pairs Applied to ABC Optimization Results.- A Game Theoretical Approach for VLSI Physical Design Placement.- Application of information systems and technologies in transport.- Online algorithms for 1-space bounded cube packing and 2-space bounded hypercube packing.