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This article investigates the current use of case studies in the teaching of Operational Research (OR) in the UK: how and where they are used; how they are developed; and whether there is an interest in training this area. It is aimed at lecturers teaching OR who are using or planning to use case studies in their teaching. It may also be of interest to policy-makers who wish to know what is being done in OR. The article focuses on the results of a survey sent to lecturers of OR in higher education in the UK. These are combined with an examination of the literature on using case studies in teaching in general and a small number of specific examples of how case studies are used in OR teaching. Case studies are included in OR teaching in a variety of ways and to develop a range of skills; particularly the ability to transfer academic knowledge to real-life contexts. The article identifies that the most significant barrier to the use of case studies in OR teaching is the development of new case studies; suggestions are made to address this, including providing training and collaboration opportunities. Overall this article provides an assessment of the ways in which case studies are used in OR; the advantages and limitations of using them; and specific examples of their use which will provide ideas to assist in improving OR teaching.

In this paper we address the clinic location selection problem for a fully integrated Sexual Health Service across Hampshire. The service provides outpatient services for Genito-Urinary Medicine, contraceptive and reproductive health, sexual health promotion and a sexual assault referral centre. We aim to assist the planning of sexual health service provision in Hampshire by conducting a location analysis using both current and predicted patient need. We identify the number of clinic locations required and their optimal geographic location that minimise patient travel time. To maximise the chances of uptake of results we validate the developed simple algorithm with an exact method as well as three well-known, but complex meta-heuristics. The analysis was conducted using car travel and public transport times. Two scenarios were considered: current clinic locations only; and anywhere within Hampshire. The results show that the clinic locations could be reduced from 28 to 20 and still keep 90% of all patient journeys by public transport (e.g. by bus or train) to a clinic within 30 minutes. The number of clinics could be further reduced to 8 if the travel time is based on car travel times within 15 minutes. Results from our simple solution method compared favourably to the exact solution as well as the complex meta-heuristics. [ABSTRACT FROM AUTHOR]