A job shop scheduling approach based on simulation optimization

Yan Yan*, Guoxin Wang

*Corresponding author for this work

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

13 Citations (Scopus)

Abstract

With regards to the problem of the traditional scheduling approach can't establish the precise scheduling models and obtain the satisfied scheduling results at the same time, a new scheduling approach based on simulation optimization methodology is presented. The approach comprises two modules: genetic algorithm (GA) based optimizer and discrete event simulation model. Candidate scheduling schemes represented by a serial of scheduling rules are suggest by GA that automatically guides the system towards better solutions. Simulation models are used to evaluate the performance of candidate scheduling schemes, the results of evaluation are returned to the GA to be utilized in selection of the next generation of candidate scheduling schemes to be evaluated. This process continues until a satisfactory solution is obtained. In addition, In order to build simulation model rapidly for the similar production conditions, a simulation modeling approach based on modular control models including shop level controller model, cell level controller model and equipment level controller model is present. The approach encompasses control logic, which are separated from the basic modeling elements in the simulation model, of different levels in production system. Finally, a case study is presented to illustrate the application of the proposed approach.

Original languageEnglish
Title of host publicationIEEM 2007
Subtitle of host publication2007 IEEE International Conference on Industrial Engineering and Engineering Management
Pages1816-1822
Number of pages7
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007 - , Singapore
Duration: 2 Dec 20074 Dec 2007

Publication series

NameIEEM 2007: 2007 IEEE International Conference on Industrial Engineering and Engineering Management

Conference

Conference2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2007
Country/TerritorySingapore
Period2/12/074/12/07

Keywords

  • Genetic algorithm
  • Scheduling
  • Simulation modeling
  • Simulation optimization

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