用于可解释预算分配的稀疏线性代理模型
Sparse Linear Surrogates for Interpretable Budget Allocation
首次发表
浏览论文内容
中文总结 AI 辅助
针对可解释预算分配问题，提出含稀疏线性规则的新型线性代理模型，给出基于混合整数规划的精确方法与启发式方法，经计算实验验证了两种方法的性能。
中文摘要 AI 辅助
为满足对固有可解释优化方法的需求，我们提出了用于预算分配问题的新型线性代理模型。这些代理模型由稀疏线性规则组成，可将实例映射到基于特征的解决方案表示。我们提出了一种基于混合整数规划的精确方法及一种用于计算的启发式方法，并通过计算实验分析了两种方法的性能。
英文摘要
To address the demand for inherently interpretable optimization methods, we introduce novel linear surrogates for budget allocation problems. These surrogates consist of sparse linear rules that map instances to feature-based representations of solutions. We present an exact approach based on mixed-integer programming as well as a heuristic for their computation. The performance of both approaches is analyzed through computational experiments.
