A genetic-algorithm-based optimization model for scheduling flexible assembly lines

Z. X. Guo, Wai Keung Wong, S. Y S Leung, J. T. Fan, S. F. Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

53 Citations (Scopus)

Abstract

In this paper, a scheduling problem in the flexible assembly line (FAL) is investigated. The mathematical model for this problem is presented with the objectives of minimizing the weighted sum of tardiness and earliness penalties and balancing the production flow of the FAL, which considers flexible operation assignments. A bi-level genetic algorithm is developed to solve the scheduling problem. In this algorithm, a new chromosome representation is presented to tackle the operation assignment by assigning one operation to multiple machines as well as assigning multiple operations to one machine. Furthermore, a heuristic initialization process and modified genetic operators are proposed. The proposed optimization algorithm is validated using two sets of real production data. Experimental results demonstrate that the proposed optimization model can solve the scheduling problem effectively.
Original languageEnglish
Pages (from-to)156-168
Number of pages13
JournalInternational Journal of Advanced Manufacturing Technology
Volume36
Issue number1-2
DOIs
Publication statusPublished - 1 Feb 2008

Keywords

  • Bi-level genetic algorithm
  • Flexible assembly line
  • Scheduling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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