Solving CSP Instances Beyond the Phase Transition Using Stochastic Search Algorithms

Authors:
Luk Schoofs;Bart Naudts
Affiliations:
-;-
Venue:
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Year:
2000

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Abstract

When solving constraint satisfaction problems (CSPs) with stochastic search algorithms (SSAs) using the standard penalty function, it is not possible to show that there is no solution for a problem instance. In this paper we present a hybrid function that can be generally used in conjunction with SSAs to prove unsolvability without changing the search algorithms drastically. We use eight state-of-the-art algorithms to show the general usability of the new function. We compare the algorithms with and without the new penalty function and we test the scalability of the new function.