Abstract
In this work we have combined two promising global optimization methods, interval arithmetic methods and genetic algorithms, into a set of hybrid algorithms that share the good properties of both methods while avoiding some drawbacks of the constituent methods. Interval aritmetic gives us some simple arithmetic methods to estimate the range of rational functions to be optimized, while genetic algorithms are able to adaptively guide the search.
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