Abstract

We study the scheduling problem of minimising weighted completion times on parallel identical batching machines with dynamic job arrivals and incompatible job families. Each job is associated with a family, weight (priority), release time, and size. Batching machines can process simultaneously up to a specified total size of the jobs of a particular family. The scheduling problem can be represented by. We present a mathematical model and heuristic algorithms employing different local search procedures individually and sequentially under a variable neighbourhood search scheme. We have shown that among local searches, repositioning the batches instead of jobs yields better results. The best-performing heuristic algorithm is capable of generating solutions within 0.6% of the best overall heuristic solution for each instance in a reasonable amount of time. When this heuristic is compared against the mathematical model, solutions that are 3.7% above optimal on average in the 15-job problem instances are possible.

Original languageEnglish (US)
Pages (from-to)2462-2477
Number of pages16
JournalInternational Journal of Production Research
Volume51
Issue number8
DOIs
StatePublished - 2013

Fingerprint

Scheduling
Heuristic algorithms
Mathematical models
Batch
Parallel machines
Batching
Heuristic algorithm
Local search
Mathematical model
Heuristics

Keywords

  • batch scheduling
  • heuristics
  • mathematical modelling
  • scheduling
  • variable neighbourhood search

ASJC Scopus subject areas

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

Cite this

Batch scheduling on parallel machines with dynamic job arrivals and incompatible job families. / Cakici, Eray; Mason, Scott J.; Fowler, John; Neil Geismar, H.

In: International Journal of Production Research, Vol. 51, No. 8, 2013, p. 2462-2477.

Research output: Contribution to journalArticle

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