Al-Azzani, M.K., Davari,S and England, T.J., 2020. an empirical investigation of forecasting methods for ambulance calls – a case study. health systems, in press.
A primary goal of emergency services is to minimise the response times to emergencies whilst managing operational costs. This paper is motivated by real data from the Welsh Ambulance Service which in recent years has been criticised for not meeting its eight-minute response target. In this study, four forecasting approaches (ARIMA, Holt Winters, Multiple Regression and Singular Spectrum Analysis (SSA)) are considered to investigate whether they can provide more accurate predictions to the call volume demand (total and by category) than the current approach on a selection of planning horizons (weekly, monthly and 3-monthly). Each method is applied to a training and test set and root mean square error (RMSE) and mean absolute percentage error (MAPE) error statistics are determined. Results showed that ARIMA is the best forecasting method for weekly and monthly prediction of demand and the long-term demand is best predicted using the SSA method.
Davari, S. and Van Woensel, T., 2020. The elderly centre location problem. Journal of the Operational Research Society, pp.1-14.
Increased human life expectancy combined with declining birth rates around the globe has led to ageing populations, particularly in the developed world. This phenomenon brings about increased dependency ratios and calls for setting new policies for the elderly citizens. This comprises provision of a set of life-enhancing services in an accessible and equitable way. In this paper, we consider the multi-period problem of locating senior centres offering these services to the elderly population with budget constraints and capacity limitations. Both consistent and inconsistent versions of the problem are considered, aiming at identifying the set of facilities to operate in each region at each period, the service type(s) to be offered and the allocation of budget in each period to location and operation of facilities. A mixed integer mathematical programming model is presented, an efficient iterated local search procedure is proposed and managerial insights are provided.
Mamaghani, E.J. and Davari, S., 2020. The bi-objective periodic closed loop network design problem. Expert Systems with Applications, 144, p.113068.
Reverse supply chains are becoming a crucial part of retail supply chains given the recent reforms in the consumers’ rights and the regulations by governments. This has motivated companies around the world to adopt zero-landfill goals and move towards circular economy to retain the product’s value during its whole life cycle. However, designing an efficient closed loop supply chain is a challenging undertaking as it presents a set of unique challenges, mainly owing to the need to handle pickups and deliveries at the same time and the necessity to meet the customer requirements within a certain time limit. In this paper, we model this problem as a bi-objective periodic location routing problem with simultaneous pickup and delivery as well as time windows and examine the performance of two procedures, namely NSGA-II and NRGA, to solve it. The goal is to find the best locations for a set of depots, allocation of customers to these depots, allocation of customers to service days and the optimal routes to be taken by a set of homogeneous vehicles to minimise the total cost and to minimise the overall violation from the customers’ defined time limits. Our results show that while there is not a significant difference between the two algorithms in terms of diversity and number of solutions generated, NSGA-II outperforms NRGA when it comes to spacing and runtime.
Davari, S., 2019. The incremental cooperative design of preventive healthcare networks. Annals of Operations Research, 272(1-2), pp.445-492.
In the Preventive Healthcare Network Design Problem (PHNDP), one seeks to locate facilities in a way that the uptake of services is maximised given certain constraints such as congestion considerations. We introduce the incremental and cooperative version of the problem, IC-PHNDP for short, in which facilities are added incrementally to the network (one at a time), contributing to the service levels. We first develop a general non-linear model of this problem and then present a method to make it linear. As the problem is of a combinatorial nature, an efficient Variable Neighbourhood Search (VNS) algorithm is proposed to solve it. In order to gain insight into the problem, the computational studies were performed with randomly generated instances of different settings. Results clearly show that VNS performs well in solving IC-PHNDP with errors not more than 1.54%.
Choudrie, J., Pheeraphuttranghkoon, S. and Davari, S., 2018. The Digital Divide and Older Adult Population Adoption, Use and Diffusion of Mobile Phones: a Quantitative Study. Information Systems Frontiers, pp.1-23.
Due to the changing demographics of societies around the world, ageing has become a major concern for governments and policy makers alike. What has also become clear is that the older adult consumer group and the factors affecting this age group have been studied relatively less in the literature. In this paper, we aim to investigate the adoption, usage, and diffusion of smartphones within the UK older adults so as to identify the factors encouraging or inhibiting smartphone usage and service provision within this age group. To this end, we propose a conceptual framework (Model of Smartphone Acceptance) based on a set of well-known theories of adoption and diffusion. We collected data from 984 participants living in north London and applied the Partial Least Square Structural Equation Modelling (PLS-SEM) technique to analyse the data. Our research can contribute towards reducing some of the existing digital divide within UK older adults. Moreover, businesses can benefit from our research by understanding the significant factors affecting the adoption of smartphones among the UK older population and to adapt their policies accordingly.
Davari, S., Kilic, K. and Naderi, S., 2016. A heuristic approach to solve the preventive health care problem with budget and congestion constraints. Applied Mathematics and Computation, 276, pp.442-453.
Preventive health care is of utmost importance to governments since they can make massive savings on health care expenditure and promote the well-being of the society. Preventive care includes many services such as cancer screenings, vaccinations, hepatitis screenings, and smoking cessation programs. Despite the benefits of these services, their uptake is not satisfactory in many countries in the world. This can be attributed to financial barriers, social issues., and other factors. One of the most important barriers for preventive care is accessibility to proper services, which is a function of various qualitative and quantitative factors such as the distance to travel, waiting time, vicinity of facilities to other attractive facilities (such as shopping malls), and even the cleanliness of the facilities. Statistics show that even a small improvement in people’s participation can save massive amounts of money for any government and improve the well-being of the people in a society. This paper addresses the problem of designing a preventive health care network considering impatient clients, and budget constraints. The objective is to maximize the accessibility of services to people. We model the problem as a mixed-integer programming problem with budget constraints, and congestion considerations. An efficient variable neighborhood search procedure is proposed and computational experiments are performed on a large set of instances.