Improvements to genetic algorithm for flexible job shop scheduling with overlapping in operations

Yiyong He, Wei Weng, Shigeru Fujimura

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

1 Citation (Scopus)

Abstract

Flexible job-shop scheduling problem (FJSP) is an extended job-shop scheduling problem. FJSP allows an operation to be processed by several different machines. FJSP with overlapping in operations means that each operation is divided into several sublots. Sublots are processed and transferred separately without waiting for the entire operation to be processed. In previous research, a mathematical model was developed and a genetic algorithm proposed to solve this problem. In this study, we try to improve the procedure of previous research to achieve better results. The proposed improvements were tested on some benchmark problems and compared with the results obtained by previous research.

Original languageEnglish
Title of host publicationProceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages791-796
Number of pages6
ISBN (Electronic)9781509055074
DOIs
Publication statusPublished - 2017 Jun 27
Event16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017 - Wuhan, China
Duration: 2017 May 242017 May 26

Other

Other16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017
CountryChina
CityWuhan
Period17/5/2417/5/26

Fingerprint

Job Shop Scheduling
Job Shop Scheduling Problem
Overlapping
Genetic algorithms
Genetic Algorithm
Entire
Mathematical Model
Mathematical models
Benchmark
Job shop scheduling
Genetic algorithm

Keywords

  • Flexible job shop
  • Genetic algorithm
  • Overlapping in operation
  • Scheduling

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Modelling and Simulation

Cite this

He, Y., Weng, W., & Fujimura, S. (2017). Improvements to genetic algorithm for flexible job shop scheduling with overlapping in operations. In Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017 (pp. 791-796). [7960100] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIS.2017.7960100

Improvements to genetic algorithm for flexible job shop scheduling with overlapping in operations. / He, Yiyong; Weng, Wei; Fujimura, Shigeru.

Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 791-796 7960100.

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

He, Y, Weng, W & Fujimura, S 2017, Improvements to genetic algorithm for flexible job shop scheduling with overlapping in operations. in Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017., 7960100, Institute of Electrical and Electronics Engineers Inc., pp. 791-796, 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017, Wuhan, China, 17/5/24. https://doi.org/10.1109/ICIS.2017.7960100
He Y, Weng W, Fujimura S. Improvements to genetic algorithm for flexible job shop scheduling with overlapping in operations. In Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 791-796. 7960100 https://doi.org/10.1109/ICIS.2017.7960100
He, Yiyong ; Weng, Wei ; Fujimura, Shigeru. / Improvements to genetic algorithm for flexible job shop scheduling with overlapping in operations. Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 791-796
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