Abstract
This chapter is an introduction to evolutionary algorithms, a commonly used method by which solutions to problems that might otherwise be impossible to solve are solved. One such method is that of the genetic algorithm. Sometimes, evolutionary algorithms are based on what is called heuristics, or rules of thumb. They are guidelines for solutions that work; there are no mathematical proofs of their effectiveness, they just work well. Consequently, methods incorporating heuristics are deemed to be “weak.” The word is unfortunate for it conveys a sense of inaccuracy or approximation, but it is, in fact, responsible for some excellent solutions. These weaker methods use less domain knowledge and are not oriented toward specific targets. In law enforcement analytics, the existence of such methods has been shown to be very advantageous.
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Buscema, M., Capriotti, M. (2013). A Brief Introduction to Evolutionary Algorithms and the Genetic Doping Algorithm. In: Buscema, M., Tastle, W. (eds) Intelligent Data Mining in Law Enforcement Analytics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4914-6_4
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