Referring to our readings about evolving and adaptive agents, we notice that most researchers proclaim the adaptivity of their systems' entities but without being able to estimate or evaluate it in a measure. Throughout this paper, we propose at first, to specify some crucial characteristics qualifying an entity (or agent) as evolving and adaptive. Since these characteristics are generally imperfect and suffer from uncertainties and inaccuracies, we propose a fuzzy rule base system (FRBS) as an intelligent method in order to estimate the measure of an adaptivity degree. We detail the fuzzy definition of selected inputs and output. Finally, we test and discuss the reliability of the suggested method on several examples, got from published works in various fields and had different characteristics.

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we investigate a real Storage Problem (SP) defined by the Tunisian company. It requires finding the minimum number of bins to pack all the available items (mattresses). Each item has a different sizes (width, height, length) and characteristics (ranges, colors, quantity). The problem is interpreted as Three-Dimensional Variable-Sized Bin Packing Problem (3D-VSBPP). Two heuristics are presented based on Best-Fit Decreasing (BFD) and Next-Fit decreasing (NFD) strategy. Those heuristics are analyzed in case; the number of bins is unlimited. The proposed approaches are analyzed on a real data with up to 9344 items and two bins types.

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