ACS-TS: Train scheduling using ant colony system
type: Item
instance of: scholarly article
title: ACS-TS: Train scheduling using ant colony system
zbMATH Open document ID: 1152.90441
DOI: 10.1155/JAMDS/2006/95060
author: Keivan Ghoseiri
author: Fahimeh Morshedsolouk
published in: Journal of Applied Mathematics and Decision Sciences
publication date: 2008-11-20T00:00:00Z
full work available at URL: https://eudml.org/doc/129494
review text: Summary: This paper develops an algorithm for the train scheduling problem using the ant colony system metaheuristic called ACS-TS. At first, a mathematical model for a kind of train scheduling problem is developed and then the algorithm based on ACS is presented to solve the problem. The problem is considered as a traveling salesman problem (TSP) wherein cities represent the trains. ACS determines the sequence of trains dispatched on the graph of the TSP. Using the sequences obtained and removing the collisions incurred, train scheduling is determined. Numerical examples in small and medium sizes are solved using ACS-TS and compared to exact optimum solutions to check for quality and accuracy. Comparison of the solutions shows that ACS-TS results in good quality and time savings. A case study is presented to illustrate the solution.
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 90B10
Mathematics Subject Classification ID: 68M10
zbMATH DE Number: 5369133
describes a project that uses: MACS-VRPTW
describes a project that uses: HAS-QAP
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 5369133