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Genetic algorithms (GAs) are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology. These are widely used in different areas of bioinformatics. In immunoinformatics, a common optimization problem is the search of optimal vaccination schedules. The problem of defining optimal schedules is particularly acute in cancer immunopreventive approaches, which requires a sequence of vaccine administrations to keep a high level of protective immunity. This paper presents a formalization of the optimization problem and show how a GA search on a model-based approach can be used to deal with the problem.