Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access


    On the Use of Genetic Algorithm for Solving Re-entrant Flowshop Scheduling with Sum-of-processing-times-based Learning Effect to Minimize Total Tardiness

    Win-Chin Lina, Chin-Chia Wua, Kejian Yub, Yong-Han Zhuanga, Shang-Chia Liuc

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 671-681, 2018, DOI:10.1080/10798587.2017.1302711

    Abstract Most research studies on scheduling problems assume that a job visits certain machines only one time. However, this assumption is invalid in some real-life situations. For example, a job may be processed by the same machine more than once in semiconductor wafer manufacturing or in a printed circuit board manufacturing machine. Such a setting is known as the “re-entrant flowshop”. On the other hand, the importance of learning effect present in many practical situations such as machine shop, in different branches of industry and for a variety of corporate activities, in shortening life cycles, and in an increasing diversity of… More >

Displaying 1-10 on page 1 of 1. Per Page  

Share Link