数据立方体选择的改进遗传算法

数据立方体选择问题是一个NP完全问题。研究了利用遗传算法来解决立方体选择问题，提出了一个结合局部搜索机制的遗传算法。这一算法的核心思想在于，首先运用一个基于单位空间最大收益值的预处理算法来生成初始解，然后该初始解经结合了局部搜索机制的遗传算法进行提高。实验结果表明，该算法在寻优性能上优于启发式算法和经典遗传算法。

Genetic Selection Algorithm for OLAP Data Cubes

The data cube selection problem is known to be an NP-hard problem. In this study, we examined the applicalion of genetic algorithms to the cube selection problem. We proposed a genetic local search algorithm. The core idea of the algorithm is as follows. First, a pre-process algorithm based on the maximum benefit per unit space was used to generate initial solutions. Then, the initial solutions were improved by genetic algorithm having the local search of optimal strategies. The experimental results show that the proposed algorithm outperforms heuristic algorithm and canonical genctic algorithm.