Construction and repair: A hybrid approach to search in CSPs

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Abstract

In order to obtain a solution to a constraint satisfaction problem, constructive methods iteratively extend a consistent partial assignment until all problem variables are instantiated. If the current partial assignment is proved to be inconsistent, it is then necessary to backtrack and perform alternative instantiations. On the other hand, reparative methods iteratively repair an inconsistent complete assignment until it becomes consistent. In this research, we investigate an approach which allows for the combination of constructive and reparative methods, in the hope of exploiting their intrinsic advantages and circumventing their shortcomings. Initially, we discuss a general hybrid method called CR and then proceed to specify its parameters in order to provide a fully operational search method called CNR. The reparative stage therein is of particular interest: we employ techniques borrowed from local search and propose a general cost function for evaluating partial assignments. In addition, we present experimental results on the open-shop scheduling problem. The new method is compared against specialized algorithms and exhibits outstanding performance, yielding solutions of high quality and even improving the best known solution to a number of instances.

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Chatzikokolakis, K., Boukeas, G., & Stamatopoulos, P. (2004). Construction and repair: A hybrid approach to search in CSPs. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3025, pp. 342–351). Springer Verlag. https://doi.org/10.1007/978-3-540-24674-9_36

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