Abstract
In this paper we present the architecture of a flexible, object-oriented Java solution framework for implementing genetic algorithms (GA) solutions to NP-hard problems. The framework realizes problem-independent features of any GA solution. Its flexibility lies in the fact that it can be easily configured with components specific to a particular solution. We discuss the classroom usage of our framework and also present how instructors can use this framework to vary the level of difficulty of a GA programming project, depending on the desired learning outcomes. Finally, we present a comparison of our framework with others that are available on the Internet.
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