Multitasking parallel-machine scheduling with machine-dependent slack due-window assignment

Min Ji, Wenya Zhang, Lijuan Liao, T. C.E. Cheng, Yuanyuan Tan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

We consider the problem of parallel-machine scheduling with machine-dependent slack (SLK) due-window assignment in the multitasking environment, which exists in various application domains such as Internet services, project management, and manufacturing. Motivated by practical observations, we extend the original model of multitasking to a more general model where each job’s interruption proportion depends on the job itself and its processing position. In the light of individualised service, we consider SLK due-window assignment. Our objective is to minimise the total cost that comprises the earliness, tardiness, and due-window-related costs. Finding that an optimal schedule exists when each machine is occupied by at least one job, we show that the problem is polynomially solvable. We provide a more efficient solution algorithm for a special case of the problem. Finally, we present numerical examples to illustrate the application of the theoretical results and working of the solution algorithms.

Original languageEnglish
Pages (from-to)1667-1684
Number of pages18
JournalInternational Journal of Production Research
Volume57
Issue number6
DOIs
Publication statusPublished - 19 Mar 2019

Keywords

  • assignment
  • multitasking
  • parallel machines
  • scheduling
  • SLK due-window

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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