Single-machine slack due-window assignment and scheduling with past-sequence-dependent delivery times and controllable job processing times

Min Ji, Danli Yao, Jiaojiao Ge, Edwin Tai Chiu Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

In this paper, we study single-machine scheduling that considers slack (SLK) due-window assignment, past-sequence-dependent delivery times and controllable job processing times simultaneously. We assume that the actual processing time of a job is a function of the learning effect on the job and resource allocation to the job and the job delivery time is proportional to its waiting time. The objective is to find jointly the optimal job sequence, optimal flow allowance value (i.e., optimal common waiting time) and optimal resource allocation to minimise a total cost comprising the earliness, tardiness, due-window-related and resource consumption costs. We consider two models of the job processing time function and provide polynomial-time solution algorithms for the corresponding problems. We also provide a more efficient solution algorithm for a special case of the problem.
Original languageEnglish
Pages (from-to)794-818
Number of pages25
JournalEuropean Journal of Industrial Engineering
Volume9
Issue number6
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • Learning effect
  • Past-sequence-dependent delivery times
  • Resource allocation
  • Scheduling
  • SLK due-window assignment

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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