We propose a binary representation of categorical values using a linear map. This linear representation preserves the neighborhood structure of categorical values. In the context of evolutionary algorithms, it means that every categorical value can be reached in a single mutation. The linear representation is embedded into standard metaheuristics, applied to the problem of Sudoku puzzles, and compared to the more traditional direct binary encoding. It shows promising results in fixed-budget experiments and empirical cumulative distribution functions with high dimension instances, and also in fixed-target experiments with small dimension instances.

翻译：我们建议使用线性地图来二进制表达绝对值。 这个线性表达法保留了绝对值的周边结构。 在进化算法中, 这意味着每个绝对值都可以在单一突变中达到。 线性表达法嵌入标准的计量经济学中, 适用于数独谜题的问题, 与更传统的直接二进制编码相比。 它显示了固定预算实验和具有高维度的经验性累积分配功能以及具有小维度的固定目标实验中的良好结果 。