Making the first solution good!

Abstract : Providing efficient black-box search procedures is one of the major concerns for constraint-programming solvers. Most of the contributions in that area follow the fail-first principle, which is very useful to close the search tree or to solve SAT/UNSAT problems. However, for real-life applications with an optimization criterion, proving optimality is often unrealistic. Instead, it is very important to compute a good solution fast. This paper introduces a value selector heuristic focusing on objective bounds to make the first solution good. Experiments show that it improves former approaches on a wide range of problems.
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Submitted on : Monday, November 6, 2017 - 10:20:20 AM
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Jean-Guillaume Fages, Charles Prud'Homme. Making the first solution good!. ICTAI 2017 29th IEEE International Conference on Tools with Artificial Intelligence, Nov 2017, Boston, MA, United States. ⟨hal-01629182⟩

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