Dynamic clusters (Dynamic Location of Phone Call Clusters)

When mobile handsets are making a call, a measurement report is sent to the serving base station periodically which includes the signal strengths to the base station and the next six strongest signals of the surrounding base stations. Motorola asked the Study Group if it was possible to say whether we could use this information to infer if phone calls occur in clusters and if it was possible to determine the locations, size and other features of these clusters. The Study Group found clusters in 'signal space,' that is, handsets reporting similar signal strengths with the same base stations and explored methods of locating these clusters geographically

Wind farm output

The problem was to devise a simulation method for the wind speeds at a set of sites, that has the correct autocorrelation, cross-correlation and distributions. The report includes one way of doing this, using a multivariate auto-regressive system, and other comments and observations that may lead to better ways of achieving the aim

Siting of HIV/AIDS diagnostic equipment in South Africa: a case study in locational analysis

This paper describes a practical application of locational analysis to the siting of HIV/AIDS diagnostic equipment in laboratories across South Africa. Classical location analytical techniques were extended to ensure that laboratories are sited as close as possible to major centres of demand from hospitals and clinics. A particular advantage of the modified set covering algorithm developed is that choices between laboratory sites are made in a transparent manner. In order to find appropriate numbers and ideal placement of CD4 laboratories, runs were undertaken for various scenarios based on maximum travel time from health facilities to laboratory sites. Results demonstrated to decision makers showed close comparisons with pilot review projects undertaken in four health districts of South Africa. The research has potential to impact health care delivery to HIV sufferers in the poorest rural regions of the country

A bi-objective optimization model for technology selection and donor’s assignment in the blood supply chain

Los procesos de toma de decisiones suponen frecuentemente más de un objetivo. En el caso de la selección de tecnologías en procesos de captación de productos sanguíneos, están en conflicto los costos de recolección asociados a la tecnología utilizada y la cantidad de donantes requeridos para la satisfacción de la demanda. De igual forma, en la cadena de suministro de sangre  este tipo de decisiones se tornan más complejas cuando se consideran las características propias del sistema, como proporcionalidad de tipos de sangre y compatibilidad entre productos. Para dar solución a este problema se propone un modelo de programación lineal entera que contiene como objetivos la minimización del costo total y del número de donantes. Este modelo está sujeto a restricciones de capacidad, proporcionalidad de tipos de sangre y satisfacción de demanda entre otras. Para la solución del modelo se utilizó Open Solver 2.1 y para la generación de las soluciones eficientes que conforman el frente de Pareto se implementó en VBA el algoritmo épsilon restricciones aumentado.Decision-making processes often contain more than one objective. In technology selection in the blood collection processes, the cost related to the collection technology and the amount of donors required to meet the demand are in conflict. In the same way, in the blood supply chains decisions become more complex when features of the system such as blood type proportions and compatibilities are considered. In order to generate solutions to this problem, an Integer Linear Programming is proposed considering total cost minimisation and amount of donors required. This model also considers distinct constraints such as capacity, proportionality, and demand fulfilment among others. Open Solver 2.1 was used to solve this problem in combination with Visual Basic for Applications for generating the set of efficient solutions that make up the Pareto front through the augmented Epsilon constraint algorithm

Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements

Introduction: CD4 testing in South Africa is based on an integrated tiered service delivery model that matches testing demand with capacity. The National Health Laboratory Service has predominantly implemented laboratory-based CD4 testing. Coverage gaps, over-/under-capacitation and optimal placement of point-of-care (POC) testing sites need investigation. Objectives: We assessed the impact of relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory and POC testing sites. Methods: The RACL algorithm was developed to allocate laboratories and POC sites to ensure coverage using a set coverage approach for a defined travel time (T). The algorithm was repeated for three scenarios (A: T = 4; B: T = 3; C: T = 2 hours). Drive times for a representative sample of health facility clusters were used to approximate T. Outcomes included allocation of testing sites, Euclidian distances and test volumes. Additional analysis included platform distribution and space requirement assessment. Scenarios were reported as fusion table maps. Results: Scenario A would offer a fully-centralised approach with 15 CD4 laboratories without any POC testing. A significant increase in volumes would result in a four-fold increase at busier laboratories. CD4 laboratories would increase to 41 in scenario B and 61 in scenario C. POC testing would be offered at two sites in scenario B and 20 sites in scenario C. Conclusion: The RACL algorithm provides an objective methodology to address coverage gaps through the allocation of CD4 laboratories and POC sites for a given T. The algorithm outcomes need to be assessed in the context of local conditions

Can you model growth of trust? A study of the sustainability of a rural community health centre in North India

Trust in the service provided by any health facility is of vital importance to its sustainability, whether it is a community clinic in a rural area of a developing country or an international telemedicine service. Community health centres can be used as a means of delivering highly accessible, low-cost health service in the developing world. A major strategic issue for planners of such centres is the expected level of uptake of services throughout a region and its effect on sustainability of any facility. In this study of a clinic in rural north India, Monte Carlo simulation is used in modelling the spatio-temporal spread of usage of the service. Trust in the provider is built both through word-of-mouth contacts and previous development activities: our study contributes to the literature with a practical application of trust modelling

An OR approach to planning sustainable community health schemes in rural areas of developing countries. poster discussion presentations: planning sustainable community health schemes in rural areas of developing countries using hierarchical location modelling.

We are attempting to bridge the gap between planning based on summarising statistics alone and the alternative of a purely soft approach based on local conditions. Amongst other OR methods, simulation of social infuence networks is planned alongside hierarchical location modelling.Difficulties abound but with open-mindedness and the benefits of collaboration with those experienced in the healthcare field, we hope to contribute to a vital arena in the search for sustainable development to benefit those marginalised in society