The current storage system is facing the bottleneck of performance due to the gap between fast CPU computing speed and the slow response time of hard disk. Recently a multitier hybrid storage system (MTHS) which uses fast flash devices like a solid-state drive (SSD) as the one of the high performance storage tiers has been proposed to boost the storage system performance. In order to maintain the overall performance of the MTHS, optimal disk storage assignment has to be designed so that the data migrated to the high performance tier like SSD is the optimal set of data. In this paper we proposed a optimal data allocation algorithm for disk storage in MTHS. The data allocation problem (DAP) is to find the optimal lists of data files for each storage tier in the MTHS to achieve maximal benefit values without exceeding the available size of each tier. We formulate the DAP as a special multiple choice knapsack problem (MCKP) and propose the multiple-stage dynamic programming (MDP) to find the optimal solutions. The results show that the MDP can achieve improvements up to 6 times compared with the existing greedy algorithms.