A bi-level genetic algorithm for multi-objective scheduling of multi- and mixed-model apparel assembly lines

  • Authors:

  • Z. X. Guo;W. K. Wong;S. Y. S. Leung;J. T. Fan;S. F. Chan

  • Affiliations:

  • Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong

  • Venue:
  • AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, a multi-objective scheduling problem of the multi- and mixed-model apparel assembly line (MMAAL) is investigated. A bi-level genetic algorithm is developed to solve the scheduling problem, in which a new chromosome representation is proposed to represent the flexible operation assignment including assigning one operation to multiple workstations as well as assigning multiple operations to one workstation. The proposed algorithm is validated using real-world production data and the experimental results show that the proposed algorithm can solve the proposed scheduling problem effectively.