A genetic-algorithm-based optimization model for solving the flexible assembly line balancing problem with work sharing and workstation revisiting

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

Research output: Journal article publicationJournal articleAcademic researchpeer-review

50 Citations (Scopus)

Abstract

This paper investigates a flexible assembly line balancing (FALB) problem with work sharing and workstation revisiting. The mathematical model of the problem is presented, and its objective is to meet the desired cycle time of each order and minimize the total idle time of the assembly line. An optimization model is developed to tackle the addressed problem, which involves two parts. A bilevel genetic algorithm with multiparent crossover is proposed to determine the operation assignment to workstations and the task proportion of each shared operation being processed on different workstations. A heuristic operation routing rule is then presented to route the shared operation of each product to an appropriate workstation when it should be processed. Experiments based on industrial data are conducted to validate the proposed optimization model. The experimental results demonstrate the effectiveness of the proposed model to solve the FALB problem.
Original languageEnglish
Pages (from-to)218-228
Number of pages11
JournalIEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
Volume38
Issue number2
DOIs
Publication statusPublished - 1 Mar 2008

Keywords

  • Assembly line balancing (ALB)
  • Genetic algorithms (GAs)
  • Optimization
  • Work sharing
  • Workstation revisiting

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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