This paper proposes a 0-1 knapsack problem considering both the maximization of the total return including randomness and minimization of available budget, simulta- neously. For the flexibility of setting each goal, the satisfaction function is introduced and the model maximizing minimum aspiration levels is proposed. Since this prob- lem is not a well-defined problem due to including randomness and fuzziness, chance constraints are introduced, and a main problem is transformed into a nonlinear 0-1 programming problem. In previous researches, the solution method using a parametric dynamic programming approach is constructed. However, this solution method is not efficient due to using dynamic programming repeatedly. Therefore, in this paper, the efficient solution method is constructed. This means that the number of using dynamic programming is as small as possible.