Improved mixed-integer linear programming model and heuristics for bi-objective single-machine batch scheduling with energy cost consideration

Shibohua Zhang, Ada Che, Xueqi Wu, Chengbin Chu

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

This article addresses bi-objective single-machine batch scheduling under time-of-use electricity prices to minimize the total energy cost and the makespan. The lower and upper bounds on the number of formed batches are first derived and a continuous-time mixed-integer linear programming model is proposed, which improves an existing discrete-time model in the literature. Two improved heuristics are proposed based on the improved model. Computational experiments demonstrate that the improved model and heuristics can run hundreds of times faster than the existing ones for large-size instances.

Original languageEnglish
Pages (from-to)1380-1394
Number of pages15
JournalEngineering Optimization
Volume50
Issue number8
DOIs
StatePublished - 3 Aug 2018

Keywords

  • bi-objective optimization
  • heuristics
  • mixed-integer linear programming (MILP)
  • Single-machine batch scheduling
  • time-of-use (TOU) electricity prices

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