Multi-objective optimization for a strategic ATM network redesign problem

Are Denstad, Einar Ulsund, Marielle Christiansen, Lars Magnus Hvattum and Gregorio Tirado ()
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Are Denstad: Norwegian University of Science and Technology
Einar Ulsund: Norwegian University of Science and Technology
Marielle Christiansen: Norwegian University of Science and Technology
Lars Magnus Hvattum: Molde University College
Gregorio Tirado: Complutense University of Madrid

Annals of Operations Research, 2021, vol. 296, issue 1, No 2, 7-33

Abstract: Abstract During the last decades, the banking industry has been facing multiple challenges, from changes in regulations and legal systems, to the irruption of new technologies. A constant adaptation to the rapidly changing business ecosystem is therefore required. This paper deals with one type of efficiency improvement that is required from traditional banking operations as a result of the current shift in the industry towards more use of technology. That is, we deal with the decision-making process related to the redesign of existing ATM networks, which is currently being considered by many banks worldwide. This redesign is mainly a consequence of an increased use of electronic payment methods and card transactions, which have made the demand for cash decrease significantly. We describe a multi-objective mathematical programming model to be used as a tool when making strategic decisions regarding the bank ATM network redesign. Total costs and the coverage of customers and turnover are considered as conflicting performance attributes and analyzed through several multi-criteria techniques, namely the weighted sum and Tchebycheff methods and Archimedean goal programming. Among other insights, the results on a realistic case study show that the potential for cost reductions is high and that the consideration of both customer coverage and turnover coverage is crucial for the performance of the network.

Keywords: Multi-criteria; Banking; Mathematical programming; Strategic planning (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10479-019-03224-z

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