Energy consumption minimization for single machine scheduling with bounded maximum tardiness

Ada Che, Ke Lv, Eugene Levner, Vladimir Kats

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

This paper investigates a single machine scheduling problem to minimize energy consumption with bounded maximum tardiness. A set of jobs are to be processed on a single machine which is speed-scalable. Each job is characterized by its release time, deadline and processing time. The machine can process only one job with some speed at a time. No preemption is allowed. Since energy consumption is associated with the processing speed, both job sequencing and speed choosing decisions have to be made. Two MILP (mixed integer linear programming) models, which respectively use dichotomous constraints and assignment constraints to model the processing sequence of jobs, are built for this problem. The models are implemented in C++ and solved by CPLEX. Computational results with randomly generated instances demonstrate that the model using assignment constraints is much more efficient than that with dichotomous constraints.

Original languageEnglish
Title of host publicationICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages146-150
Number of pages5
ISBN (Electronic)9781479980697
DOIs
StatePublished - 1 Jun 2015
Event2015 12th IEEE International Conference on Networking, Sensing and Control, ICNSC 2015 - Taipei, Taiwan, Province of China
Duration: 9 Apr 201511 Apr 2015

Publication series

NameICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control

Conference

Conference2015 12th IEEE International Conference on Networking, Sensing and Control, ICNSC 2015
Country/TerritoryTaiwan, Province of China
CityTaipei
Period9/04/1511/04/15

Keywords

  • energy consumption
  • maximum tardiness
  • scheduling
  • single machine
  • speed scaling

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