Ant Colony Optimization for Train Scheduling: An Analysis
Автор: Sudip Kumar Sahana, Aruna Jain, Prabhat Kumar Mahanti
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 2 vol.6, 2014 года.
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This paper deals on cargo train scheduling between source station and destination station in Indian railways scenario. It uses Ant Colony Optimization (ACO) technique which is based on ant’s food finding behavior. Iteration wise convergence process and the convergence time for the algorithm are studied and analyzed. Finally, the run time analysis of Ant Colony Optimization Train Scheduling (ACOTS) and Standard Train Scheduling (STS) algorithm has been performed.
Ant Colony Optimization, Train Scheduling Problem, Pheromone, State Transition Rule, Local Pheromone Update Rule, Global Pheromone Update Rule
Короткий адрес: https://sciup.org/15010525
IDR: 15010525
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