An Improved Model for Parallel Machine Scheduling under Time-of-Use Electricity Price

Junheng Cheng, Feng Chu, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

A recent study has led to an interesting mixed-integer linear programming (MILP) model for parallel machine scheduling under time-of-use (TOU) tariffs, which assumes great importance in achieving sustainable economic development. In this paper, we provide an improved MILP model by significantly reducing the number of decision variables. The computational results show that the performance of the improved model is superior to that of the existing one.

Original languageEnglish (US)
Pages (from-to)896-899
Number of pages4
JournalIEEE Transactions on Automation Science and Engineering
Volume15
Issue number2
DOIs
StatePublished - Apr 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Mixed-integer linear programming (MILP)
  • parallel machine scheduling
  • time-of-use (TOU) tariffs
  • total electricity cost

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