We describe a nonstandard genetic algorithm approach to the nonlinear transportation problem. This extends our earlier research for the linear transportation problem. New “chromosome structures” and “genetic operators” are introduced to preserve feasibility. Results seem promising. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

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In R v T [2010] EWCA Crim 2439, [2011] 1 Cr App Rep 85, the Court of Appeal indicated that ‘mathematical formulae’, such as likelihood ratios, should not be used by forensic scientists to analyse data where firm statistical evidence did not exist. Unfortunately, when considering the forensic scientist's evidence, the judgment consistently commits a basic logical error, the ‘transposition of the conditional’ which indicates that the Bayesian argument has not been understood and extends the confusion surrounding it. The judgment also fails to distinguish between the validity of the relationships in a formula and the precision of the data. We explain why the Bayesian method is the correct logical method for analysing forensic scientific evidence, how it works and why ‘mathematical formulae’ can be useful even where firm statistical data is lacking.

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