Two-agent two-machine flowshop scheduling with learning effects to minimize the total completion time

Yau Ren Shiau, Ming Shua Tsai, Wen Chiung Lee, Edwin Tai Chiu Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

28 Citations (Scopus)

Abstract

We study a two-agent scheduling problem in a two-machine permutation flowshop with learning effects. The objective is to minimize the total completion time of the jobs from one agent, given that the maximum tardiness of the jobs from the other agent cannot exceed a bound. We provide a branch-and-bound algorithm for the problem. In addition, we present several genetic algorithms to obtain near-optimal solutions. Computational results indicate that the algorithms perform well in either solving the problem or efficiently generating near-optimal solutions.
Original languageEnglish
Pages (from-to)580-589
Number of pages10
JournalComputers and Industrial Engineering
Volume87
DOIs
Publication statusPublished - 29 Jun 2015

Keywords

  • Learning effects
  • Scheduling
  • Total completion time
  • Two agent
  • Two-machine flowshop

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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