A railway company in Japan is required to plan further efficient passenger transportation and to reduce costs because of competition with intercity express buses and a decline in passenger. Optimization of a railway rolling stock planning possibly provides the reduction of purchase cost of a new train unit and maintenance costs of owning units. This paper proposes a new approach based on Ant Colony Optimization (ACO) to solve railway rolling stock planning. The effectiveness of the proposed method is demonstrated through numerical experiments with instance data made from the railway lines in Kyushu Railway Company (JR Kyushu).
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