ATM Location Problem and Cash Management in Automated Teller Machines
Automated Teller Machines (ATMs) can be
considered among one of the most important service facilities in the
banking industry. The investment in ATMs and the impact on the
banking industry is growing steadily in every part of the world. The
banks take into consideration many factors like safety, convenience,
visibility, and cost in order to determine the optimum locations of
ATMs. Today, ATMs are not only available in bank branches but
also at retail locations. Another important factor is the cash
management in ATMs. A cash demand model for every ATM is
needed in order to have an efficient cash management system. This
forecasting model is based on historical cash demand data which is
highly related to the ATMs location. So, the location and the cash
management problem should be considered together. This paper
provides a general review on studies, efforts and development in
ATMs location and cash management problem.
[1] E.D. Hatzakis, S.K. Nair, M.L. Pinedo, "Operations in financial
services—an overview", Production and Operations Management, vol.
19(6), pp.633-664, 2010.
[2] P. Adams, "Choosing a Choice ATM Site; ATM Buyer's Guide", Credit
Union Management, vol. 14 (3), pp.15-17, 1991.
[3] A. Quadrei, S. Habib, "Allocation of heterogeneous banks’ Automated
Teller Machines", In: 2009 First International Conference on Intensive
Applications and Services, April 21-25, 2009, pp.16-21, Valencia.
[4] M.A. Aldajani, H.K. Alfares, "Location of banking Automatic Teller
Machines based on convolution", Computers & Industrial Engineering,
vol. 57, pp.1194-1201, 2009.
[5] O. Berman, R.C. Larson, N. Fouska, "Optimal location of discretionary
service facilities", Transportation Science, vol. 26 (3), pp.201–211,
1992.
[6] P.V. Boufounou, "Theory and methodology evaluating bank branch
location and performance: a case study", European Journal of
Operational Research, vol. 87, pp.389-402, 1995.
[7] H. Min, E. Melachrinoudis, "The three-hierarchical location-allocation
of banking facilities with risk and uncertainty", International
Transactions in Operational Research, vol.8, pp.381-401, 2001.
[8] V. Jayaraman, R. Gupta, H. Pirkul, "Selecting hierarchical facilities in a
service-operations environment", European Journal of Operational
Research, vol. 147, pp.613-628, 2003.
[9] L. Zhang, G. Rushton, "Optimizing the size and locations of facilities in
competitive multi-site service systems", Computers & Operations
Research, vol. 35, pp.327-338, 2008.
[10] Y. Li, H. Sun, C. Zhang, G. Li, "Sites selection of ATMs based on
particle swarm optimization", In: 2009 International Conference on
Information Technology and Computer Science, July 25-26, 2009,
pp.526-530, Kiev.
[11] L. Zi-fa, Z. Wei, J Xing, L. Ke, "Optimal planning of charging station
for electric vehicle based on particle swarm optimization", In:
Innovative Smart Grid Technologies – Asia, May 21-24, 2012, pp. 1-5,
Tianjin.
[12] J. Castro, "A stochastic programming approach to cash management in
banking", European Journal of Operational Research. vol. 192, pp.963-
974, 2009.
[13] R. Simutis, D. Dilijonas, L. Bastina, "Cash demand forecasting for ATM
using neural networks and support vector regression algorithms", In:
20th EURO Mini Conference Continuous Optimization and Knowledge-
Based Technologies, May 20-23, 2008, pp. 416-421, Neringa.
[14] H. Snellman, M. Viren, "ATM networks and cash usage applied
financial economics", vol. 19, pp.841-851, 2009.
[15] R. Armenise, C. Birtolo, E. Sangianantoni, L. Troiano, "A generative
solution for ATM cash management", In: 2010 International Conference
of Soft Computing and Pattern Recognition, December 7-10, 2010,
pp.349-356, Paris.
[16] S.D. Teddy, S.K. Ng,. "Forecasting ATM cash demands using a local
learning model of cerebellar associative memory network", International
Journal of Forecasting, vol. 27, pp.760-776, 2011.
[17] R. Simutis, D. Dilijonas, L. Bastina, J. Friman, P. Drobinov,
"Optimization of cash management for ATM network", Information
Technology and Control, vol. 36 (1A), pp.117-121, 2007.
[18] A. Laukaitis, "Functional data analysis for cash flow and transactions
intensity continuous-time prediction using Hilbert-valued autoregressive processes", European Journal of Operational Research, vol. 185,
pp.1607–1614, 2008.
[19] A.R. Brentnall, M.J. Crowder, D.J. Hand, "Predictive-sequential
forecasting system development for cash machine stocking",
International Journal of Forecasting, vol. 26, pp.764-776, 2010a.
[20] A.R. Brentnall, M.J. Crowder, D.J. Hand, "Predicting the amount
individuals withdraw at cash machines using a random effects
multinomial model", Statistical Modeling, vol. 10 (2), pp.197-214,
2010b.
[21] S. Ben Taieb, G. Bontempi, A.F. Atiya, A. Sorjamaa, "A review and
comparison of strategies for multi-step ahead time series forecasting
based on the NN5 forecasting competition", Expert Systems with
Applications, vol. 39, pp. 7067–7083, 2012.
[22] G. Acuña, C. Ramirez, M. Curilem, "Comparing NARX and NARMAX
models using ANN and SVM for cash demand forecasting for ATM",
In: WCCI 2012 IEEE World Congress on Computational Intelligence,
June 10-15, 2012, Brisbane.
[23] R.G. Van Anholt, L.C. Coelho, G. Laporte, I.F.A. Vis, "An inventoryrouting
problem with pickups and deliveries arising in the replenishment
of automated teller machines", Research paper, CIRRELT-2013-71,
2013.
[24] S. Chotayakul, P. Charnsetthikul, J. Pichitlamken, J. Kobza, "An
optimization-based heuristic for a capacitated lot-sizing model in an
automated teller machines network", Journal of Mathematics and
Statistics, vol. 9(4), pp. 283–288, 2013.
[25] T. Baker, V. Jayaraman, N. Ashley, "A data-driven inventory control
policy for cash logistics operations: An exploratory case study
application at a financial institution", Decision Sciences, vol.44 (1), pp.
205–226, 2013.
[26] Y. Ekinci, J-C. Lu, E. Duman, "Optimization of ATM cash
replenishment with group-demand forecasts", Expert Systems with
Applications, vol. 42, pp. 3480-3490, 2015.
[1] E.D. Hatzakis, S.K. Nair, M.L. Pinedo, "Operations in financial
services—an overview", Production and Operations Management, vol.
19(6), pp.633-664, 2010.
[2] P. Adams, "Choosing a Choice ATM Site; ATM Buyer's Guide", Credit
Union Management, vol. 14 (3), pp.15-17, 1991.
[3] A. Quadrei, S. Habib, "Allocation of heterogeneous banks’ Automated
Teller Machines", In: 2009 First International Conference on Intensive
Applications and Services, April 21-25, 2009, pp.16-21, Valencia.
[4] M.A. Aldajani, H.K. Alfares, "Location of banking Automatic Teller
Machines based on convolution", Computers & Industrial Engineering,
vol. 57, pp.1194-1201, 2009.
[5] O. Berman, R.C. Larson, N. Fouska, "Optimal location of discretionary
service facilities", Transportation Science, vol. 26 (3), pp.201–211,
1992.
[6] P.V. Boufounou, "Theory and methodology evaluating bank branch
location and performance: a case study", European Journal of
Operational Research, vol. 87, pp.389-402, 1995.
[7] H. Min, E. Melachrinoudis, "The three-hierarchical location-allocation
of banking facilities with risk and uncertainty", International
Transactions in Operational Research, vol.8, pp.381-401, 2001.
[8] V. Jayaraman, R. Gupta, H. Pirkul, "Selecting hierarchical facilities in a
service-operations environment", European Journal of Operational
Research, vol. 147, pp.613-628, 2003.
[9] L. Zhang, G. Rushton, "Optimizing the size and locations of facilities in
competitive multi-site service systems", Computers & Operations
Research, vol. 35, pp.327-338, 2008.
[10] Y. Li, H. Sun, C. Zhang, G. Li, "Sites selection of ATMs based on
particle swarm optimization", In: 2009 International Conference on
Information Technology and Computer Science, July 25-26, 2009,
pp.526-530, Kiev.
[11] L. Zi-fa, Z. Wei, J Xing, L. Ke, "Optimal planning of charging station
for electric vehicle based on particle swarm optimization", In:
Innovative Smart Grid Technologies – Asia, May 21-24, 2012, pp. 1-5,
Tianjin.
[12] J. Castro, "A stochastic programming approach to cash management in
banking", European Journal of Operational Research. vol. 192, pp.963-
974, 2009.
[13] R. Simutis, D. Dilijonas, L. Bastina, "Cash demand forecasting for ATM
using neural networks and support vector regression algorithms", In:
20th EURO Mini Conference Continuous Optimization and Knowledge-
Based Technologies, May 20-23, 2008, pp. 416-421, Neringa.
[14] H. Snellman, M. Viren, "ATM networks and cash usage applied
financial economics", vol. 19, pp.841-851, 2009.
[15] R. Armenise, C. Birtolo, E. Sangianantoni, L. Troiano, "A generative
solution for ATM cash management", In: 2010 International Conference
of Soft Computing and Pattern Recognition, December 7-10, 2010,
pp.349-356, Paris.
[16] S.D. Teddy, S.K. Ng,. "Forecasting ATM cash demands using a local
learning model of cerebellar associative memory network", International
Journal of Forecasting, vol. 27, pp.760-776, 2011.
[17] R. Simutis, D. Dilijonas, L. Bastina, J. Friman, P. Drobinov,
"Optimization of cash management for ATM network", Information
Technology and Control, vol. 36 (1A), pp.117-121, 2007.
[18] A. Laukaitis, "Functional data analysis for cash flow and transactions
intensity continuous-time prediction using Hilbert-valued autoregressive processes", European Journal of Operational Research, vol. 185,
pp.1607–1614, 2008.
[19] A.R. Brentnall, M.J. Crowder, D.J. Hand, "Predictive-sequential
forecasting system development for cash machine stocking",
International Journal of Forecasting, vol. 26, pp.764-776, 2010a.
[20] A.R. Brentnall, M.J. Crowder, D.J. Hand, "Predicting the amount
individuals withdraw at cash machines using a random effects
multinomial model", Statistical Modeling, vol. 10 (2), pp.197-214,
2010b.
[21] S. Ben Taieb, G. Bontempi, A.F. Atiya, A. Sorjamaa, "A review and
comparison of strategies for multi-step ahead time series forecasting
based on the NN5 forecasting competition", Expert Systems with
Applications, vol. 39, pp. 7067–7083, 2012.
[22] G. Acuña, C. Ramirez, M. Curilem, "Comparing NARX and NARMAX
models using ANN and SVM for cash demand forecasting for ATM",
In: WCCI 2012 IEEE World Congress on Computational Intelligence,
June 10-15, 2012, Brisbane.
[23] R.G. Van Anholt, L.C. Coelho, G. Laporte, I.F.A. Vis, "An inventoryrouting
problem with pickups and deliveries arising in the replenishment
of automated teller machines", Research paper, CIRRELT-2013-71,
2013.
[24] S. Chotayakul, P. Charnsetthikul, J. Pichitlamken, J. Kobza, "An
optimization-based heuristic for a capacitated lot-sizing model in an
automated teller machines network", Journal of Mathematics and
Statistics, vol. 9(4), pp. 283–288, 2013.
[25] T. Baker, V. Jayaraman, N. Ashley, "A data-driven inventory control
policy for cash logistics operations: An exploratory case study
application at a financial institution", Decision Sciences, vol.44 (1), pp.
205–226, 2013.
[26] Y. Ekinci, J-C. Lu, E. Duman, "Optimization of ATM cash
replenishment with group-demand forecasts", Expert Systems with
Applications, vol. 42, pp. 3480-3490, 2015.
@article{"International Journal of Business, Human and Social Sciences:71175", author = "M. Erol Genevois and D. Celik and H. Z. Ulukan", title = "ATM Location Problem and Cash Management in Automated Teller Machines", abstract = "Automated Teller Machines (ATMs) can be
considered among one of the most important service facilities in the
banking industry. The investment in ATMs and the impact on the
banking industry is growing steadily in every part of the world. The
banks take into consideration many factors like safety, convenience,
visibility, and cost in order to determine the optimum locations of
ATMs. Today, ATMs are not only available in bank branches but
also at retail locations. Another important factor is the cash
management in ATMs. A cash demand model for every ATM is
needed in order to have an efficient cash management system. This
forecasting model is based on historical cash demand data which is
highly related to the ATMs location. So, the location and the cash
management problem should be considered together. This paper
provides a general review on studies, efforts and development in
ATMs location and cash management problem.", keywords = "ATM location problem, cash management problem,
ATM cash replenishment problem, literature review in ATMs.", volume = "9", number = "7", pages = "2543-6", }
