Multi-Criteria Optimization in Answer Set Programming
Multi-Criteria Optimization in Answer Set Programming
复制标题
答案集编程中的多标准优化
DOI：
--
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Torsten Schaub
中科院分区：
文献类型：
--
作者：
M. Gebser;Roland Kaminski;B. Kaufmann;Torsten Schaub
我们阐述了用回答集编程(ASP)解决多准则优化问题的新策略和启发式算法。特别是，我们设想了一种新的求解算法，该算法基于冲突驱动学习，允许在优化过程中非均匀下降。我们将这些技术应用于解决实际的Linux包配置问题。为此，我们描述了Linux包配置工具aspcud，并将其性能与寻求替代方法的系统进行了比较。
We elaborate upon new strategies and heuristics for solving multi-criteria optimization problems via Answer Set Programming (ASP). In particular, we conceive a new solving algorithm, based on conflict-driven learning, allowing for non-uniform descents during optimization. We apply these techniques to solve realistic Linux package configuration problems. To this end, we describe the Linux package configuration tool aspcud and compare its performance with systems pursuing alternative approaches.