A multi-objective ant colony optimization method applied to switch engine scheduling in railroad yards

Pesquisa Operacional

Jodelson A. Sabino²  José Eugênio Leal¹  Thomas Stützle¹  Mauro Birattari¹ 

[1] ,PUC-Rio Dep. de Engenharia Industria Rio de Janeiro RJ ,Brazil

关键词: ACO;    ant colony optimization;    railroad yard operational planning;    switch engine scheduling;    ACO;    otimização com colônia de formigas;    planejamento operacional de pátios ferroviários;    planejamento de operações de locomotivas de manobra;   

DOI  :  10.1590/S0101-74382010000200013

来源: SciELO

【 摘 要 】

This paper proposes an ant colony optimization algorithm to assist railroad yard operational planning staff in their daily tasks. The proposed algorithm tries to minimize a multi-objective function that considers both fixed and variable transportation costs involved in moving railroad cars within the railroad yard area. This is accomplished by searching the best switch engine schedule for a given time horizon. As the algorithm was designed for real life application, the solution must be delivered in a predefined processing time and it must be in accordance with railroad yard operational policies. A railroad yard operations simulator was built to produce artificial instances in order to tune the parameters of the algorithm. The project is being developed together with industrial professionals from the Tubarão Railroad Terminal, which is the largest railroad yard in Latin America.

【 授权许可】

CC BY   
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