Hallo! Tracked shipping to Netherlands with Delivery Duty Paid for just €7 

Ship to
Netherlands
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada A Brief Introduction to Continuous Evolutionary Optimization
Type
Physical Book
Author
Publisher
Language
English
Pages
94
Format
Paperback
Dimensions
23.4x15.6x0.6 cm
Weight
0.16 kg.
ISBN13
9783319034218
Categories

A Brief Introduction to Continuous Evolutionary Optimization

Oliver Kramer (Author) · Springer · Paperback

A Brief Introduction to Continuous Evolutionary Optimization - Kramer, Oliver

Cheaper New Book Imported to Netherlands
Delivery: 02 Oct - 09 Oct Shipping: 13 to 17 business days.
€ 53,83
Faster New Book Imported to Netherlands
Delivery: 23 Sep - 25 Sep Shipping: 6 to 7 business days.
€ 69,02
Import costs and 9% BTW included in the price ✅
€ 53,83

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "A Brief Introduction to Continuous Evolutionary Optimization"

Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the problem is available except via function evaluations. This work introduces a collection of heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. The book gives an introduction to evolution strategies and parameter control. Heuristic extensions are presented that allow optimization in constrained, multimodal and multi-objective solution spaces. An adaptive penalty function is introduced for constrained optimization. Meta-models reduce the number of fitness and constraint function calls in expensive optimization problems. The hybridization of evolution strategies with local search allows fast optimization in solution spaces with many local optima. A selection operator based on reference lines in objective space is introduced to optimize multiple conflictive objectives. Evolutionary search is employed for learning kernel parameters of the Nadaraya-Watson estimator and a swarm-based iterative approach is presented for optimizing latent points in dimensionality reduction problems. Experiments on typical benchmark problems as well as numerous figures and diagrams illustrate the behavior of the introduced concepts and methods.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews