In the process of iterative software development, the project team need to determine the features that should be added to the system as part of the next release. This problem is named the next release problem (NRP). Usually, the solutions of NRP base on empirical tools and give the quasi-optimal solution. Every feature of the software system is characterized by its importance and complexity so that the NRP can be formulated as the bi-objective optimization problem. The objective of the paper is to modify the algorithm of combinations enumeration for finding the Pareto-optimal solution for NRP, reducing the time and cost of required computing resources. We consider three versions of the algorithm of combinations enumeration. It is shown that the algorithm of combinations enumeration with filtering is the best algorithm accordingly of criteria of computation time and memory consumption.