Ant Colony Optimization for Train Scheduling: An Analysis

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Sudip Kumar Sahana 1,* Aruna Jain 2 Prabhat Kumar Mahanti 3

1. Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India

2. Department of Information Technology, Birla Institute of Technology, Mesra, Ranchi, India

3. Department of Computer Science & Applied Statistics, University of New Brunswick, Canada

* Corresponding author.


Received: 4 May 2013 / Revised: 20 Sep. 2013 / Accepted: 15 Nov. 2013 / Published: 8 Jan. 2014

Index Terms

Ant Colony Optimization, Train Scheduling Problem, Pheromone, State Transition Rule, Local Pheromone Update Rule, Global Pheromone Update Rule


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.

Cite This Paper

Sudip Kumar Sahana, Aruna Jain, Prabhat Kumar Mahanti, "Ant Colony Optimization for Train Scheduling: An Analysis", International Journal of Intelligent Systems and Applications(IJISA), vol.6, no.2, pp.29-36, 2014. DOI:10.5815/ijisa.2014.02.04


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