Open Access   Article Go Back

A Study on Optimize Skip Stop Service Using Genetic Algorithm in Selected Indian Railway Division

Soumya Sengupta1 , Amartya Neogi2

Section:Survey Paper, Product Type: Journal Paper
Volume-3 , Issue-7 , Page no. 124-128, Jul-2015

Online published on Jul 30, 2015

Copyright © Soumya Sengupta , Amartya Neogi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Soumya Sengupta , Amartya Neogi , “A Study on Optimize Skip Stop Service Using Genetic Algorithm in Selected Indian Railway Division,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.7, pp.124-128, 2015.

MLA Style Citation: Soumya Sengupta , Amartya Neogi "A Study on Optimize Skip Stop Service Using Genetic Algorithm in Selected Indian Railway Division." International Journal of Computer Sciences and Engineering 3.7 (2015): 124-128.

APA Style Citation: Soumya Sengupta , Amartya Neogi , (2015). A Study on Optimize Skip Stop Service Using Genetic Algorithm in Selected Indian Railway Division. International Journal of Computer Sciences and Engineering, 3(7), 124-128.

BibTex Style Citation:
@article{Sengupta_2015,
author = {Soumya Sengupta , Amartya Neogi },
title = {A Study on Optimize Skip Stop Service Using Genetic Algorithm in Selected Indian Railway Division},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2015},
volume = {3},
Issue = {7},
month = {7},
year = {2015},
issn = {2347-2693},
pages = {124-128},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=587},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=587
TI - A Study on Optimize Skip Stop Service Using Genetic Algorithm in Selected Indian Railway Division
T2 - International Journal of Computer Sciences and Engineering
AU - Soumya Sengupta , Amartya Neogi
PY - 2015
DA - 2015/07/30
PB - IJCSE, Indore, INDIA
SP - 124-128
IS - 7
VL - 3
SN - 2347-2693
ER -

VIEWS PDF XML
2327 2232 downloads 2387 downloads
  
  
           

Abstract

Railway authorities aim to provide transportation service to the customer in a safe as well as effective and efficient manner. The main constraints forcing them to regulate their service are the limitation of resources. This paper found the optimal coordination of stopping stations that can increase and improve overall benefits of skip stop service. A skip stop pattern must find an optimal balance between faster passenger travel time and lower service frequencies at each station. The main objective is to optimize passenger travel time with maintaining railway and infrastructural behavior.

Key-Words / Index Term

Genetic Algorithm, Indian Railway, SkipStop Service , Optimization

References

[1] Assad, A.A., 1980. Models for rail transportation. Transportation Research Part A: General 14 (3), 205–220.
[2] Cordeau, J.F., Toth, P., Vigo, D., 1998. A survey of optimization models for routing and scheduling. Transportation Science 32 (4), 380– 404.
[3] Fay, A., 2000. A fuzzy knowledge-based system for railway traffic control. Engineering Applications of Artificial Intelligence 13 (6), 719–729.
[4] Peeters L, Kroon L (2000) A cycle based optimization model for the cyclic railway timetabling problem. In: Voss S, Daduna J (eds) Computer-Aided Scheduling of Public Transport, Springer, Berlin.
[5] Li, F., Z. Gao, K. Li, and L. Yang. 2008. “Efficient Scheduling of Railway Traffic Based on Global Information of Train.” Transportation Research Part B 42:1008–1030.
[6] J.-C. Jong, C.-S. Suen and S. J. Chang, "A Decision Support System to Optimize Railway Stopping Patterns: Application To The Taiwan High Speed Rail," in Transportation Research Board 91st Annual Meeting, Washington D.C., 2011.
[7] Corman, F., D’Ariano, A., Pacciarelli, D., Pranzo, M., 2010. Centralized versus distributed systems to reschedule trains in two dispatching areas. Public Transport: Planning and Operations 2 (3), 219–247.
[8] Acuna-Agost, R., Michelon, P., Feillet, D., Gueye, S., 2011. SAPI: Statistical Analysis of Propagation of Incidents. A new approach for rescheduling trains after disruptions. European Journal of Operational Research 215 (1), 227– 243.
[9] Tnquist Krasemann, J., 2012. Design of an effective algorithm for fast response to the re-scheduling of railway traffic during disturbances. Transportation Research Part C 20 (1), 62–78.