高效任意时间算法求解双目标下一版本发布问题
Efficient anytime algorithms to solve the bi-objective Next Release Problem
AI总结：
针对双目标下一版本发布问题，提出五种任意时间算法，在搜索过程中维持分布良好的解集，支持决策者随时停止，并能找到受支持和非受支持的解，时间充足时可完成完整帕累托前沿。
摘要：
下一版本发布问题是指从软件产品的需求集合中选取一个子集，用于在下一版本中开发。该选择应在满足需求约束的前提下，最大化利益相关者的满意度并最小化开发成本。近期的工作使用基于整数线性规划的精确方法解决了该问题。在实践中，无需计算问题的所有有效解；在目标空间中分布良好的解集对决策者更为便利。过去用于寻找完整帕累托前沿的精确方法以字典序方式探索目标空间，或使用目标的加权和来求解单目标问题，但只能找到受支持的解。在本工作中，我们提出了五种新方法，这些方法在搜索过程中的任何时刻都维持一个分布良好的解集，以便决策者在找到足够大的解集时可以停止算法。由于这一特性，这些方法被称为任意时间算法。它们能够找到受支持和非受支持的解，并且如果提供的时间足够长，可以完成整个帕累托前沿。
英文摘要：
The Next Release Problem consists in selecting a subset of requirements to develop in the next release of a software product. The selection should be done in a way that maximizes the satisfaction of the stakeholders while the development cost is minimized and the constraints of the requirements are fulfilled. Recent works have solved the problem using exact methods based on Integer Linear Programming. In practice, there is no need to compute all the efficient solutions of the problem; a well-spread set in the objective space is more convenient for the decision maker. The exact methods used in the past to find the complete Pareto front explore the objective space in a lexicographic order or use a weighted sum of the objectives to solve a single-objective problem, finding only supported solutions. In this work, we propose five new methods that maintain a well-spread set of solutions at any time during the search, so that the decision maker can stop the algorithm when a large enough set of solutions is found. The methods are called anytime due to this feature. They find both supported and non-supported solutions, and can complete the whole Pareto front if the time provided is long enough.
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