Designing guide-path networks for automated guided vehicle system by using the Q-learning technique

  • Authors:
  • Jae Kook Lim;Joon Mook Lim;Kazuho Yoshimoto;Kap Hwan Kim;Teruo Takahashi

  • Affiliations:
  • Institute of Asia-Pacific Studies, Waseda University, Sodai-Nishiwaseda Building 6F. 1-21-1 Nishiwaseda Shinjuku-ku, Tokyo 169-0051, Japan;Department of Industrial and Management Systems Engineering, School of Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku-ku, Tokyo 169-8555, Japan;Department of Industrial and Management Systems Engineering, School of Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku-ku, Tokyo 169-8555, Japan;Department of Industrial Engineering, Pusan National University, Changjeon-dong, Kumjeong-ku, Pusan 609-735, South Korea;Institute of Asia-Pacific Studies, Waseda University, Sodai-Nishiwaseda Building 6F. 1-21-1 Nishiwaseda Shinjuku-ku, Tokyo 169-0051, Japan

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2003

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Abstract

This paper suggests a Q-learning technique for designing guide-path networks for automated guided vehicle systems. This study uses the total travel time as the decision criteria for constructing guide-path layouts. The Q-learning technique is applied to the estimation of the travel time of vehicles on each segment of the guide-path. Computational experiments were performed to evaluate the performance of the proposed algorithm. The simulation results showed that the proposed algorithm is superior to Kim and Tanchoco's (1993) in terms of average travel time, interference time, and number of deliveries.