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: Managing Intermittent Demand
  name:
    name part: Engelmeyer, Torben.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XV, 157 p. 65 illus. online resource.
  abstract: This work aims to increase the service level and to reduce the inventory costs by combining the forecast and inventory model into one consistent forecast-based inventory model. This new model is based on the prediction of the future probability distribution by assuming an integer-valued autoregressive process as demand process. The developed algorithms can be used to identify, estimate, and predict the demand as well as optimize the inventory decision of intermittent demand series. In an extensive simulation study the new model is compared with a wide range of conventional forecast/inventory model combinations. By using the consistent approach, the mean inventory level is lowered whereas the service level is increased. Additionally, a modern multi-criteria inventory classification scheme is presented to distinguish different demand series clusters. Contents Classification Approaches to Identify Intermittent Demand Series Consistent Forecast-Based Inventory Model Extensive Comparison of the Inventory Performance Among Different Forecast/Inventory Model Combinations Target Group Students and researchers interested in business analytics and operations management Inventory managers and supply chain experts The Author Dr. Torben Engelmeyer works as a research assistant at the chair of International Economics - University of Wuppertal, Germany.
  table of contents: Classification Approaches to Identify Intermittent Demand Series -- Consistent Forecast-Based Inventory Model -- Extensive Comparison of the Inventory Performance Among Different Forecast/Inventory Model Combinations.
  note: by Torben Engelmeyer.
  subject:
    topic: Business
  subject:
    topic: Business logistics
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Business and Management
  subject:
    topic: Logistics
  subject:
    topic: Supply Chain Management
  subject:
    topic: Operation Research/Decision Theory
  classification: HD38.5
  classification: 658.5
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783658140625
  identifier: http://dx.doi.org/10.1007/978-3-658-14062-5
  record info:
    record creation date: 160502
    record change date: 20160502075526.0
    record identifier: 978-3-658-14062-5