Machine scheduling with deteriorating jobs and DeJong's learning effect

Min Ji, Xiaoying Tang, Xin Zhang, Edwin Tai Chiu Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)

Abstract

We consider parallel-machine scheduling with deteriorating jobs and DeJong's learning effect. We focus on the problems to minimize the total completion time and the makespan. We show that the former is polynomially solvable, while the latter is NP-hard, for which we provide a fully polynomial-time approximation scheme.
Original languageEnglish
Pages (from-to)42-47
Number of pages6
JournalComputers and Industrial Engineering
Volume91
DOIs
Publication statusPublished - 1 Jan 2016

Keywords

  • DeJong's learning effect
  • FPTAS
  • Job deterioration
  • Scheduling

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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