TY - GEN
T1 - Ant Colony Optimization approach for solving rolling stock planning for passenger trains
AU - Tsuji, Yasutaka
AU - Kuroda, Masahiro
AU - Kitagawa, Yukiya
AU - Imoto, Yoshitaka
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - Railway rolling stock planning is a basic scheduling in railway transport, which assigns physical train units to given time table services and determines a roster of the train units. This planning also involves a scheduling of periodical inspection for the train units. We have proposed an Ant Colony Optimization (ACO) based approach to solve this planning problem. In this paper, local search methods are introduced to enhance the proposed ACO's performance for tackling a large-scale problem. The effectiveness of the enhanced ACO is demonstrated through numerical experiments with instance problems made from real railway lines.
AB - Railway rolling stock planning is a basic scheduling in railway transport, which assigns physical train units to given time table services and determines a roster of the train units. This planning also involves a scheduling of periodical inspection for the train units. We have proposed an Ant Colony Optimization (ACO) based approach to solve this planning problem. In this paper, local search methods are introduced to enhance the proposed ACO's performance for tackling a large-scale problem. The effectiveness of the enhanced ACO is demonstrated through numerical experiments with instance problems made from real railway lines.
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U2 - 10.1109/SII.2012.6427319
DO - 10.1109/SII.2012.6427319
M3 - Conference contribution
AN - SCOPUS:84874232838
SN - 9781467314961
T3 - 2012 IEEE/SICE International Symposium on System Integration, SII 2012
SP - 716
EP - 721
BT - 2012 IEEE/SICE International Symposium on System Integration, SII 2012
T2 - 2012 IEEE/SICE International Symposium on System Integration, SII 2012
Y2 - 16 December 2012 through 18 December 2012
ER -