提高有界最大和算法求解软硬约束DCOP问题的解质量
Improving Solution Quality of Bounded Max-Sum Algorithm to Solve DCOPs involving Hard and Soft Constraints
摘要：
Bounded Max-Sum（BMS）是一种消息传递算法，它为一种特定形式的分散式协调问题，即分布式约束优化问题（DCOPs）提供近似解。特别地，BMS算法能够以低计算成本为代价来解决具有大搜索空间的这种类型的问题。值得注意的是，传统的DCOP公式不考虑那些必须满足的约束（也称为硬约束），而是只关注软约束。因此，尽管在许多现实世界的应用中观察到这两种类型的约束的存在，BMS算法并不主动利用硬约束。为了解决这个问题，我们定制BMS在这样一种方式，可以处理DCOP具有两个类型的约束。这样做，我们的方法提高了算法的解决方案的质量。实证结果表明，大型DCOP的解决方案的质量有显着改善。
英文摘要：
Bounded Max-Sum (BMS) is a message-passing algorithm that provides approximation solution to a specific form of de-centralized coordination problems, namely Distributed Constrained Optimization Problems (DCOPs). In particular, BMS algorithm is able to solve problems of this type having large search space at the expense of low computational cost. Notably, the traditional DCOP formulation does not consider those constraints that must be satisfied(also known as hard constraints), rather it concentrates only on soft constraints. Hence, although the presence of both types of constraints are observed in a number of real-world applications, the BMS algorithm does not actively capitalize on the hard constraints. To address this issue, we tailor BMS in such a way that can deal with DCOPs having both type constraints. In so doing, our approach improves the solution quality of the algorithm. The empirical results exhibit a marked improvement in the quality of the solutions of large DCOPs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
