Stephen Gilmour

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For solving combinatorial optimisation problems, exact methods accurately exploit the structure of the problem but are tractable only up to a certain size; approximation or heuristic methods are tractable for very large problems but may possibly be led into a bad solution. A question that arises is, From where can we obtain knowledge of the problem(More)
We conducted a systematic review and meta-analysis of population-based cohort studies of maternal body mass index (BMI) and risk of adverse birth and health outcomes in low- and middle-income countries. PubMed, Embase, CINAHL and the British Nursing Index were searched from inception to February 2014. Forty-two studies were included. Our study found that(More)
OBJECTIVE To investigate the risk of adverse pregnancy outcomes and caesarean section among adolescents in low- and middle-income countries. DESIGN Secondary analysis using facility-based cross-sectional data from the World Health Organization (WHO) Global Survey on Maternal and Perinatal Health. SETTING Twenty-three countries in Africa, Latin America,(More)
Ant Colony Optimization (ACO) is a collection of meta-heuristics inspired by foraging in ant colonies, whose aim is to solve combinatorial optimization problems. We identify some principles behind the metaheuristics' rules; and we show that ensuring their application, as a correction to a published algorithm for the vertex cover problem, leads to a(More)
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