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: Equipment Selection for Mining: With Case Studies
  name:
    name part: Burt, Christina N.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Caccetta, Louis.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 155 p. 38 illus., 24 illus. in color. online resource.
  abstract: This unique book presents innovative and state-of-the-art computational models for determining the optimal truck-loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today's highly sophisticated and accurate mathematical-based computational models. The authors' approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applying the optimization methodology developed here can substantially improve their competitiveness.
  table of contents: Introduction -- Literature Review -- Match Factor Extensions -- Case Studies -- Single Location Equipment Selection -- Multiple Locations Equipment Selection -- Utilisation-based Equipment Selection -- Accurate Costing of Mining Equipment -- Future Research Directions.
  note: edited by Christina N. Burt, Louis Caccetta.
  subject:
    topic: Transportation engineering
  subject:
    topic: Traffic engineering
  subject:
    topic: Computational intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Transportation Technology and Traffic Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence
  classification: TA1001-1280
  classification: HE331-380
  classification: 629.04
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Systems, Decision and Control, 150
  identifier: 9783319762555
  identifier: https://doi.org/10.1007/978-3-319-76255-5
  record info:
    record creation date: 180302
    record change date: 20191022032824.0
    record identifier: 978-3-319-76255-5