Rule driven multi objective dynamic scheduling by data envelopment analysis and reinforcement learning

Xili Chen, Xinchang Hao, Hao Wen Lin, Tomohiro Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

This paper presents a rule driven method of developing composite dispatching rule for multi objective dynamic scheduling. Data envelopment analysis is adopted to select elementary dispatching rules, where each rule is justified as efficient for optimizing specific operational objectives of interest. The selected rules are subsequently combined into a single composite rule using the weighted aggregation manner. An intelligent agent is trained using reinforcement learning to acquire the scheduling knowledge of assigning the appropriate weighting values for building the composite rule to cope with the WIP fluctuation of a machine. Implementation of the proposed method in a two objective dynamic job shop scheduling problem is demonstrated and the results are satisfactory.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Automation and Logistics, ICAL 2010
Pages396-401
Number of pages6
DOIs
Publication statusPublished - 2010 Nov 17
Event2010 IEEE International Conference on Automation and Logistics, ICAL 2010 - Shatin, Hong Kong
Duration: 2010 Aug 162010 Aug 20

Publication series

Name2010 IEEE International Conference on Automation and Logistics, ICAL 2010

Conference

Conference2010 IEEE International Conference on Automation and Logistics, ICAL 2010
CountryHong Kong
CityShatin
Period10/8/1610/8/20

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Keywords

  • Composite dispatching rule
  • Data envelopment analysis
  • Dynamic job shop
  • Multi objective scheduling
  • Reinforcement learning

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Chen, X., Hao, X., Lin, H. W., & Murata, T. (2010). Rule driven multi objective dynamic scheduling by data envelopment analysis and reinforcement learning. In 2010 IEEE International Conference on Automation and Logistics, ICAL 2010 (pp. 396-401). [5585316] (2010 IEEE International Conference on Automation and Logistics, ICAL 2010). https://doi.org/10.1109/ICAL.2010.5585316