Minimising makespan heuristics for scheduling a single batch machine processing machine with non-identical job sizes

Yoon Ho Lee, Young Hoon Lee

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this paper, the problem of minimising maximum completion time on a single batch processing machine is studied. A batch processing is performed on a machine which can simultaneously process several jobs as a batch. The processing time of a batch is determined by the longest processing time of jobs in the batch. The batch processing machine problem is encountered in many manufacturing systems such as burn-in operations in the semiconductor industry and heat treatment operations in the metalworking industries. Heuristics are developed by iterative decomposition of a mixed integer programming model, modified from the successive knapsack problem by Ghazvini and Dupont (1998, Minimising mean flow times criteria on a single batch processing machine with non-identical jobs sizes. International Journal of Production Economics 55: 273-280) and the waste of batch clustering algorithm by Chen, Du, and Huang (2011, Scheduling a batch processing machine with non-identical job sizes: a clustering perspective. International Journal of Production Research 49 (19): 5755-5778). Experimental results show that the suggested heuristics produce high-quality solutions comparable to those of previous heuristics in a reasonable computation time.

Original languageEnglish
Pages (from-to)3488-3500
Number of pages13
JournalInternational Journal of Production Research
Volume51
Issue number12
DOIs
Publication statusPublished - 2013 Jun 1

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Scheduling
Integer programming
Processing
Clustering algorithms
Industry
Heat treatment
Semiconductor materials
Decomposition
Economics
Batch processing machine
Batch
Makespan
Heuristics

All Science Journal Classification (ASJC) codes

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

Cite this

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