Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm

J. Y. Tan*, Abdul Rahman, M. A.A. Rahman, M. R. Salleh, P. Bilge

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Downloads (Pure)

Abstract

A significant issue for the production sector was the complicated scheduling requirement due to shorter product life cycles and unexpected fluctuations. Scheduling has a significant effect on the ability of a manufacturing system to meet the deadlines and the schedule should be reactive to resolve disturbances during operation. Yet, job shop scheduling issues are nondeterministic polynomial time - hard (NP-hard). This research will address some aspects of combining simulation and optimization-based algorithms for job-shop scheduling and rescheduling of flexible production systems. The predictive part determines the feasible schedule to be used for a flow shop which is generated using a combination of rule-based simulation and optimization: first, using the optimization algorithm to compute a rough plan, followed by using a rule based simulation system to locally fine tune the plan to obtain the final schedule. The schedule obtained will be implemented to the real-world system which is adapted by the reactive part of the system. The results had proved that the predictive-reactive scheduling can effectively increase the effectiveness of flexible production system. It would be a promising approach to combine the advantages of simulation with optimization algorithm.

Original languageEnglish
JournalJournal of Advanced Manufacturing Technology
Volume14
Issue number3
Early online date30 Dec 2020
Publication statusEarly online date - 30 Dec 2020
Externally publishedYes

Bibliographical note

Funding Information:
Authors are grateful to Universiti Teknikal Malaysia Melaka for the financial support through FRGS/1/2017/TK03/FKP-SMC/F00342.

Publisher Copyright:
© 2020. All Rights Reserved.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • Genetic Algorithm
  • Job-Shop Scheduling
  • Optimization
  • Predictive-Reactive
  • Simulation

ASJC Scopus subject areas

  • Software
  • Automotive Engineering
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Industrial and Manufacturing Engineering
  • Management of Technology and Innovation

Fingerprint Dive into the research topics of 'Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm'. Together they form a unique fingerprint.

Cite this