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The chapter concludes that search methods inspired by insights from random problems like randomization and restarts offer a promising new way to tackle hard computational problems.
And is it stronger or weaker in terms of its resistance to failure because of random problems or actual attack.
The random problems of each size are generated 10 times, and thus, we have totally 100 random problems.
This chapter reviews a research in constraint programming (CP) and related areas involving random problems.
It discusses that random problems have proved useful in a number of different ways.
Random problems will continue to be a useful tool in understanding problem hardness.
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Given the maddeningly random problem of wines contaminated by cork taint, it's easy for consumers to wonder why the entire industry has not moved to screw caps.
Reliability analysis includes model error and other random problem parameters like steel and concrete strengths, and dead and live loads.
We evaluate structural quality of six real-world and one random problem instances, using MCA and ECA multi-objective approach.
More specifically, in our model, instead of directly sending original problem φ, we use some disguising techniques to transform original problem φ into a random problem ϕ, then outsource problem ϕ to a cloud server.
Our experimental results on random problem instances and many instances from the max-SAT libraries show that our new solver outperforms most of the existing exact max-SAT solvers, with orders of magnitude of improvement in many cases.
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