Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

Ji Bo Wang, Ming Zheng Wang, Ping Ji

Research output: Journal article publicationJournal articleAcademic researchpeer-review

47 Citations (Scopus)


In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1<a<0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.
Original languageEnglish
Pages (from-to)861-868
Number of pages8
JournalInternational Journal of Systems Science
Issue number5
Publication statusPublished - 1 May 2012


  • deteriorating jobs
  • learning effect
  • scheduling
  • single machine
  • total completion time

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications

Cite this