• DocumentCode
    2910515
  • Title

    Differential Evolution Algorithm for the Earliness/Tardiness Hybrid Flow-shop Scheduling Problem

  • Author

    Zhonghua, Han ; Haibo, Shi ; Chang, Liu

  • Author_Institution
    Dept. of Automated Equip., CAS, Shenyang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    21-22 Nov. 2009
  • Firstpage
    188
  • Lastpage
    193
  • Abstract
    In this paper, DE algorithm is presented to solve the earliness tardiness (E/T) hybrid flow-shop scheduling problem (HFSP). The mathematical model of E/T based on DE is constructed and the key application steps in DE are also discussed in detail. In the implement process of the method, DE is used to take global optimization and find which machine the jobs should be assigned on in each stage, which is also called the process route of the job; then the local assignment rules are used to determine the job´s starting time in each stage, and on the premise of satisfying the expectation completion time, the sum of earliness and tardiness penalties should be the minimum. Finally, simulation result shows the effectiveness of the method presented in this paper.
  • Keywords
    evolutionary computation; flow shop scheduling; differential evolution algorithm; earliness-tardiness hybrid flow-shop scheduling problem; expectation completion time; local assignment rules; mathematical model; tardiness penalties; Automation; Chemical industry; Content addressable storage; Information technology; Job shop scheduling; Mathematical model; Metals industry; Optimization methods; Processor scheduling; Scheduling algorithm; Differential Evolution; Earliness/Tardiness Scheduling; Hybrid flow-shop scheduling problem; Just In Time;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.147
  • Filename
    5369035