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: Optimization in Engineering
    sub title: Models and Algorithms
  name:
    name part: Sioshansi, Ramteen.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Conejo, Antonio J.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XV, 412 p. 71 illus., 26 illus. in color. online resource.
  abstract: This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.
  table of contents: 1. Optimization is Ubiquitous -- 2. Linear Optimization -- 3. Mixed-Integer Linear Optimization -- 4. Nonlinear Optimization -- 5. Iterative Solution Algorithms for Nonlinear Optimization -- 6. Dynamic Optimization -- A. Taylor Approximations and Definite Matrices -- B. Convexity -- Index.
  note: by Ramteen Sioshansi, Antonio J. Conejo.
  subject:
    topic: Mathematics
  subject:
    topic: Mathematical optimization
  subject:
    topic: Industrial engineering
  subject:
    topic: Production engineering
  subject:
    topic: Mathematics
  subject:
    topic: Optimization
  subject:
    topic: Industrial and Production Engineering
  classification: QA402.5-402.6
  classification: 519.6
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Optimization and Its Applications, 120
  identifier: 9783319567693
  identifier: http://dx.doi.org/10.1007/978-3-319-56769-3
  record info:
    record creation date: 170624
    record change date: 20170625021232.0
    record identifier: 978-3-319-56769-3