On-Line Analytical Processing(OLAP) refers to the technologies that allow users to efficiently retrieve data from the data warehouse for decision support purposes. Data warehouses tend to be extremely large. Queries tend to be complex and ad hoc, often requiring computationally expensive operations such as multi-table joins and aggregation. To solve this problem, a novel pre-aggregation algorithm, MDHEGA (Grouping Aggregation based on the Multi-dimension Hierarchical Encoding), is proposed in this paper. By using the small multi-dimension hierarchical encoding and their prefix path, MDHEGA can rapidly retrieve the matching dimension hierarchical encoding and evaluate the set of query ranges for each dimension. As a result, the algorithm can greatly reduce the disk I/Os and highly improve the efficiency of OLAP queries. The analytical and experimental results show that the MDHEGA algorithm proposed in this paper is more efficient than other existed ones.