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Multi-objective genetic algorithm for energy-efficient job shop scheduling

  • Gökan May
  • , Bojan Stahl
  • , Marco Taisch
  • , Vittal Prabhu
  • Pennsylvania State University

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Pages (from-to)7071-7089
Number of pages19
JournalInternational Journal of Production Research
Volume53
Issue number23
DOIs
StatePublished - Dec 2 2015
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  4. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

ASJC Scopus Subject Areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Keywords

  • energy efficiency
  • genetic algorithms
  • job shop
  • machine control policies
  • scheduling
  • sustainable manufacturing

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