The invention relates to the technical field of knapsack problem solving, and discloses a method for solving a bounded knapsack problem based on an improved dynamic programming algorithm, and the method comprises the steps of defining the maximum number of article types as N, the maximum capacity of a knapsack as C, the article types as i, i being greater than or equal to 0 and less than or equalto N, the single value of each article as vi, the weight as wi, and the number of each article is ki; defining an (N + 1) * (C + 1) two-dimensional value table f, the knapsack capacity is j, and j islarger than or equal to 0 and smaller than or equal to C; and calculating a remainder a, grouping the capacity states j according to the capacity remainder a, and calculating the capacity states j with the same capacity remainder in one group. According to the invention, the capacity states j are grouped according to the remainder, a traditional dynamic programming recursion formula is improved, redundant calculation brought by the BKP solving process is reduced, meanwhile, parallelization is conducted on the improved algorithm, and compared with an existing algorithm, the method has higher efficiency and can achieve rapid solving of the BKP along with increase of the data volume.