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Recent Advances in Computational Optimization

Editat de Stefka Fidanova
en Limba Engleză Paperback – 30 noi 2021
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.
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Specificații

ISBN-13: 9783030588861
ISBN-10: 3030588866
Pagini: 212
Ilustrații: X, 199 p. 90 illus., 56 illus. in color.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.33 kg
Ediția:1st ed. 2021
Editura: Springer
Locul publicării:Cham, Switzerland

Cuprins

Validation and optimization of dam break flood risk mapping based on field test cases in Armenia.- Fire Simulator capable to analyze fire spread in real time with limited field 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 Influence 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.

Textul de pe ultima copertă

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 and other domains can be formulated as optimization problems.

Caracteristici

Shows how to develop algorithms for real-world problems based on new metaheuristic methods Addresses important real-world problems Presents a comprehensive collection of extended contributions from the 12th International Workshop on Computational Optimization (WCO) held in Leipzig, Germany, September 1–4, 2019

Recenzii

“I would recommend this book both to practitioners interested in solving real-life optimization problems and to mathematicians and computer scientists developing and/or improving optimization algorithms. The plethora of application examples will help readers better understand the breadth of possible applications, teach them a few tricks that they will be able to use, and, by emphasizing remaining challenges, encourage future research.” (V. Kreinovich, Computing Reviews, November, 2016)