YuraK wrote No, the problem is NP complete, which means that no algorithm in the world today can guarantee that a feasible solution exists for an arbitrary dataset in reasonable time. More info for this old, 1 billion dollar question: http://en.wikipedia.org/wiki/P_versus_NP_problem But that doesn't mean we can't answer that question fast with good accuracy: 1) Run planner in real-time. See last part of this video: http://vimeo.com/25902052 2) Add new data as soon as it comes in 3a) If the real-time planner finds a feasible solution, notify the user that it's ok. Like in the video, this should be in milliseconds on seconds. There are no false positives. 3b) If the real-time planner doesn't find a feasible solution in 5 seconds, notify the user that it's not ok. This might be a false negative, but if you'd let a human planner do the same task, he would output far more false negatives. YuraK wrote No (see wikipedia link above). No algorithm today will be able to answer that with 100% accuracy in reasonable time as the problem scales out. But given some time, planner can easily get to a 99% accuracy. How much time? That depends on your use case: Use Planner's Benchmarker toolkit to prove by sampling that you have such an accuracy. YuraK wrote -- View this message in context: http://drools.46999.n3.nabble.com/Existence-of-feasible-solution-for-plan... Sent from the Drools: User forum mailing list archive at Nabble.com.