Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine

Yuan Yuan Lu, Jian Jin, Ping Ji, Ji Bo Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)


The focus of this paper is to analyze unrelated parallel-machine resource allocation scheduling problem with learning effect and deteriorating jobs. The goal is to find the optimal sequence of jobs and the optimal resource allocation separately for minimizing the cost function including the total load, the total completion time, the total absolute deviation of completion time and the total resource cost. We show that the problem is polynomial time solvable if the number of machines is a given constant.
Original languageEnglish
Pages (from-to)1993-2000
Number of pages8
JournalNeural Computing and Applications
Issue number7
Publication statusPublished - 1 Oct 2016


  • Deteriorating jobs
  • Learning effect
  • Parallel machine
  • Resource allocation
  • Scheduling

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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