Multi-objective optimisation in the retail banking industry with stochastic discrete-event simulation

How can the service level of the researched ATM network, operated by the particular bank, be maximised at minimum cost using industrial engineering techniques?Final year project (BEng)--Stellenbosch University, 2011.ENGLISH ABSTRACT: Cash management is a multi-objective optimisation problem which aims to maximise the service level provided to customers at minimum cost. The topic of du Toit's (2011) masters thesis was automated teller machice (ATM) cash management for a specific South African retail bank. Focus was placed on an ATM network which primarily provides cash to blue collar laborers in the rural Eastern Cape. The aim of this final year project is to refine the work done by du Toit through the specific investigation into the effect of applying a combination of the vehicle routing problem (VRP) and continuous review policy for inventory management to the retail banking industry. A decision support system (DSS) in the form of a stochastic, discrete-event simulation model is developed. 90 different scenarios are experimented with using the DSS. Results show that the application of the VRP consistently yields high service levels at low cost when compared to two other routing approaches: first-in- first-out routing and direct replenishment. It is concluded that use of the VRP is especially beneficial when the bank has substantial control over transportation cost. The principal recommendation is therefore that cost control should be maximised to fully exploit the advantages obtainable from effective cash management. Finally, it is argued that the benefits to be gained from effective cash management (higher service levels at lower cost) can lead to the improvement of the lives of many a South African wage earner. These benefits could also lead to an increased profit margin - life is all about choices.AFRIKAANSE OPSOMMING: Kontantbestuur is multi-doelstelling optimeringsprobleem waarvan die doelwit is om die diensvlak wat aan kliënte gelewer word, te maksimeer, terwyl koste minimeer word. Die onderwerp van du Toit (2011) se meesters tesis was outomatiese tellermasjien (OTM) kontantbestuur vir 'n spesifieke Suid-Afrikaanse kleinhandelbank. Fokus is geplaas op 'n OTM netwerk wat hoofsaaklik kontant aan arbeiders in die landelike Oos-Kaap voorsien. Die doel van hierdie finale jaar projek is om du Toit se werk te verfyn deur spesifiek ondersoek in te stel na die effek wat die toepassing wat 'n kombinasie van die voertuigskeduleringsprobleem en die deurlopende hersieningsbeleid vir voorraadbestuur sal hê. 'n Stogastiese, diskrete-gebeurtenis simulasie model is ontwikkel om as besluitnemings ondersteuningstelsel te dien. 90 verskillende eksperimente is met die simulasie model voltooi. Resultate toon dat die toepassing van die voertuigskeduleringsprobleem deurlopend hoë diensvlakke teen vergelykende lae koste tot gevolg het. Die voertuigskeduleringsprobleem word vergelyk met twee ander skeduleringstegnieke: eerste-in-eerste-uit skedulering en direkte aanvulling. Die gevolgtrekking word gemaak dat gebruik van die voertuigskeduleringsprobleem veral voordelig is wanneer die bank aansienlike beheer oor vervoerkoste het. Die hoof aanbeveling is daarom dat kostebeheer gemaksimeer behoort te word om ten volle munt te slaan uit die voordele wat moontlik gemaak word deur effektiewe kontantbestuur. Ten slotte word daar aangevoer dat die voordele wat sal volg uit effektiewe kontantbestuur (hoër diensvlakke teen laer koste), die lewens van vele Suid-Afrikaanse loonwerkers kan verbeter. Die voordele kan ook lei tot 'n vergrote winsmarge -- die lewe is vol keuses

The Team Orienteering Problem with Overlaps : An Application in Cash Logistics

The team orienteering problem (TOP) aims at finding a set of routes subject to maximum route duration constraints that maximize the total collected profit from a set of customers. Motivated by a real-life automated teller machine cash replenishment problem that seeks for routes maximizing the number of bank account holders having access to cash withdrawal, we investigate a generalization of the TOP that we call the team orienteering problem with overlaps (TOPO). For this problem, the sum of individual profits may overestimate the real profit. We present exact solution methods based on column generation and a metaheuristic based on large neighborhood search to solve the TOPO. An extensive computational analysis shows that the proposed solution methods can efficiently solve synthetic and real-life TOPO instances. Moreover, the proposed methods are competitive with the best algorithms from the literature for the TOP. In particular, the exact methods can find the optimal solution of 371 of the 387 benchmark TOP instances, 33 of which are closed for the first time

Index Polices for Patient Scheduling and ATM Replenishment

Markov Decision Processes (MDP) are one of the most commonly used stochastic models to solve sequential decision making problems. The optimal solution to many real-world problems cannot be achieved due to the curse of dimensionality. It is common to use a heuristic policy called the index policy, which is obtained by applying one-step policy improvement to a simple initial policy. The index policy performs close to the optimal policy and is easily implementable, which makes it attractive to use in practice. In this dissertation, we first introduce the background information on MDP and index policies in Chapter 1. We then study their applications in two problems: the appointment scheduling problem with patient preferences, and the automated teller machine (ATM) replenishment problem. In Chapter 2, we build an MDP model to design appointment scheduling policies in the presence of patient preferences. We model the patient preferences by assuming that each patient has a set of appointment days that are equally acceptable to the patient. We consider a service provider which receives the appointment-booking requests and makes an appointment decision one at a time. The objective is to minimize the long-run average cost while responding to the patients' booking requests based on their preferences. We propose the index policy and show it performs close to the optimal policy in the two-day horizon and outperforms other benchmarks in the multi-day horizon. In Chapter 3, we build an MDP model to design ATM replenishment schedules, while balancing the cost of replenishments and the cost of stock-outs. We propose a method to establish a relationship between the service level and the cost of a stock-out. We also assume that the replenishment cost is a sub-modular function of the set of ATMs that are replenished together. We derive the index policy, prove it has the same structural properties as the optimal policy, and show it performs close to the optimal policy when there are two or three ATMs. When there are a large number of ATMs, we show the index policy outperforms a benchmark policy through a simulation study and a real-world data-set.Doctor of Philosoph

Operational research and artificial intelligence methods in banking

Supplementary materials are available online at https://www.sciencedirect.com/science/article/pii/S037722172200337X?via%3Dihub#sec0031 .Copyright © 2022 The Authors. Banking is a popular topic for empirical and methodological research that applies operational research (OR) and artificial intelligence (AI) methods. This article provides a comprehensive and structured bibliographic survey of OR- and AI-based research devoted to the banking industry over the last decade. The article reviews the main topics of this research, including bank efficiency, risk assessment, bank performance, mergers and acquisitions, banking regulation, customer-related studies, and fintech in the banking industry. The survey results provide comprehensive insights into the contributions of OR and AI methods to banking. Finally, we propose several research directions for future studies that include emerging topics and methods based on the survey results

A hybrid evolutionary algorithm for vehicle routing problem with stochastic demands

In this work we propose a hybrid dynamic programming evolutionary algorithm to solve the vehicle routing problem with stochastic demands, it is a well known NP-hard problem where uncertainty enhances the computational efforts required to obtain a feasible and near-optimal solution. We develop an evolutionary technique where a rollout dynamic programming algorithm is applied as local search method to improve the quality of solutions. Motivated by computational considerations, the rollout algorithm can be applied partially, so, this finds competitive solutions in large instances for which the global rollout dynamic programming strategy is time unfeasible.Resumen. En este trabajo se propone un algoritmo evolutivo hibrido que combina un m ́etodo de programación dinámica estocástica para resolver el problema de enrutamiento de vehículos con demandas estocásticas, este es un problema demostrado como NP-difícil donde la presencia de incertidumbre incrementa los requerimientos computacionales necesarios para obtener soluciones factibles y cercanas a la óptima. Así, para el algoritmo evolutivo desarrollado se aplico un algoritmo rollout de programación dinámica estocástica como operador de búsqueda local para mejorar la calidad de las soluciones. Motivado por requerimientos computacionales, el algoritmo de rollout puede ser aplicado parcialmente, con el objetivo de encontrar soluciones competitivas en instancias lo suficientemente grandes para las cuales la estrategía global no es aplicable por consumir una cantidad de tiempo no tolerable.Maestrí

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes