A theoretical Approach to Efficient Maximal/Minimal Enumeration Algorithm and its Applications

最大（最小）解是那些不包括在（不包括）其他解中的解。一般来说，最大（最小）解的计数并不容易，因为它们通常没有相邻关系。在这项研究中，我们研究了有效的计划，枚举的算法技术，如反向搜索和稀疏性的使用的基础上。因此，我们开发了有效的枚举算法的多目标优化问题，完美序列，稠密子图，模糊频繁项集，距离遗传图。

Maximal (minimal) solutions are those not included in (not including) other solutions. Generally speaking, enumeration of maximal (minimal) solutions is not easy since they usually have no neighboring relations. In this research, we research efficient schemes of enumeration based on algorithmic technologies such as reverse search and the use of sparsity. As a result, we developed efficient enumeration algorithms for multi criteria optimization problem, perfect sequence, dense subgraph, ambiguous frequent itemset, and distance hereditary graphs.