Simultaneous selection and scheduling with sequence-dependent setup times, lateness penalties, and machine availability constraint: Heuristic approaches

M.H. Zarei, M. Davvari, F. Kolahan, Kuan Yew Wong

Research output: Contribution to journalArticle

2 Citations (Scopus)
3 Downloads (Pure)

Abstract

Job selection and scheduling are among the most important decisions for production planning in today’s manufacturing systems. However, the studies that take into account both problems together are scarce. Given that such problems are strongly NP-hard, this paper presents an approach based on two heuristic algorithms for simultaneous job selection and scheduling. The
objective is to select a subset of jobs and schedule them in such a way that the total net profit is maximized. The cost components considered include jobs' processing costs and weighted earliness/tardiness penalties. Two heuristic algorithms; namely scatter search (SS) and simulated annealing (SA), were employed to solve the problem for single machine environments. The algorithms were applied to several examples of different sizes with sequence-dependent setup times. Computational results were compared in terms of quality of solutions and convergence speed. Both algorithms were found to be efficient in solving the problem. While SS could provide solutions with slightly higher quality for large size problems, SA could achieve solutions in a more reasonable computational time.
Original languageEnglish
Pages (from-to)147-160
Number of pages14
JournalInternational Journal of Industrial Engineering Computations
Volume7
Issue number1
Early online date2 Jul 2015
DOIs
Publication statusPublished - 2016
Externally publishedYes

Bibliographical note

Growing ScienceTM is a Canadian online publisher of open access academic and scientific journals.

Keywords

  • Job selection
  • Job scheduling
  • Earliness
  • Tardiness
  • Lateness
  • Sequence-dependent setup time
  • Scatter search
  • Simulated annealing

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