Selecting the appropriate requirements to develop in the next release of an open market software product under evolution, is a compulsory step of each software development project. This selection should be done by maximizing stakeholders' satisfaction and minimizing development costs, while keeping constraints. In this work we investigate what is the requirements interactions impact when searching for solutions of the bi-objective Next Release Problem. In one hand, these interactions are explicitly included in two algorithms: a branch and bound algorithm and an estimation of distribution algorithm (EDA). And on the other, we study the performance of these not previously used solving approaches by applying them in several instances of small, medium and large size data sets. We find that interactions inclusion do enhance the search and when time restrictions exists, as in the case of the bi-objective Next Release Problem, EDAs have proven to be stable and reliable locating a large number of solutions on the reference Pareto front.

翻译：在下一次演进型开放市场软件产品版本发布中选择合适的需求进行开发，是每个软件开发项目的必要步骤。该选择需在满足约束条件的同时，最大化利益相关者满意度并最小化开发成本。本文研究需求间交互对求解双目标下一版本问题的影响。一方面，我们将这些交互显式嵌入两种算法：分支定界算法与分布估计算法（EDA）；另一方面，通过在不同规模（小、中、大型）数据集实例上应用这些尚未被采用的求解方法，评估其性能表现。研究发现：纳入交互关系确实能提升搜索性能，且在存在时间限制（如双目标下一版本问题场景）时，分布估计算法展现出稳定可靠的特性，能够定位参考帕累托前沿上的大量解。