In real world, many optimization problems are dynamic, which means that their model elements vary with time. These\nproblems have received increasing attention over time, especially from the viewpoint of metaheuristics methods. In this context,\nexperimentation is a crucial task because of the stochastic nature of both algorithms and problems. Currently, there are several\ntechnologies whose methods, problems, and performance measures can be implemented.However, in most of them, certain features\nthat make the experimentation process easy are not present. Examples of such features are the statistical analysis of the results and a\ngraphical user interface (GUI) that allows an easy management of the experimentation process. Bearing in mind these limitations,\nin the present work, we present DynOptLab, a software tool for experimental analysis in dynamic environments. DynOptLab has\ntwo main components: (1) an object-oriented framework to facilitate the implementation of new proposals and (2) a graphical\nuser interface for the experiment management and the statistical analysis of the results. With the aim of verifying the benefits of\nDynOptLab�s main features, a typical case study on experimentation in dynamic environments was carried out.
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