rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Deterministic Global Optimization
    sub title: An Introduction to the Diagonal Approach
  name:
    name part: Sergeyev, Yaroslav D.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Kvasov, Dmitri E.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 136 p. 39 illus. online resource.
  abstract: This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimization algorithms are discussed. Theoretical considerations are illustrated through engineering applications. Extensive numerical testing of algorithms described in this book stretches the likelihood of establishing a link between mathematicians and practitioners. The authors conclude by describing applications and a generator of random classes of test functions with known local and global minima that is used in more than 40 countries of the world. This title serves as a starting point for students, researchers, engineers, and other professionals in operations research, management science, computer science, engineering, economics, environmental sciences, industrial and applied mathematics to obtain an overview of deterministic global optimization. .
  table of contents: 1. Lipschitz global optimization -- 2. One-dimensional algorithms and their accleration -- 3. Diagonal approach and efficient paritioning strategies -- 4. Global optimization algorithms based on the non-redundant partitions -- References. .
  note: by Yaroslav D. Sergeyev, Dmitri E. Kvasov.
  subject:
    topic: Computer science
  subject:
    topic: Computer programming
  subject:
    topic: Computer science
    topic: Mathematics
  subject:
    topic: Computer mathematics
  subject:
    topic: Mathematical optimization
  subject:
    topic: Computer Science
  subject:
    topic: Programming Techniques
  subject:
    topic: Optimization
  subject:
    topic: Mathematics of Computing
  subject:
    topic: Mathematical Applications in Computer Science
  classification: QA76.6-76.66
  classification: 005.11
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Optimization
  identifier: 9781493971992
  identifier: http://dx.doi.org/10.1007/978-1-4939-7199-2
  record info:
    record creation date: 170617
    record change date: 20171101141957.0
    record identifier: 978-1-4939-7199-2