A generalized genetic algorithm-based solver for very large jigsaw puzzles of complex types

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Abstract

In this paper we introduce new types of square-piece jigsaw puzzles, where in addition to the unknown location and orientation of each piece, a piece might also need to be flipped. These puzzles, which are associated with a number of real world problems, are considerably harder, from a computational standpoint. Specifically, we present a novel generalized genetic algorithm (GA)- based solver that can handle puzzle pieces of unknown location and orientation (Type 2 puzzles) and (two- sided) puzzle pieces of unknown location, orientation, and face (Type 4 puzzles). To the best of our knowledge, our solver provides a new state-of-the-art, solving previously attempted puzzles faster and far more accurately, handling puzzle sizes that have never been attempted before, and assembling the newly introduced two-sided puzzles automatically and effectively. This paper also presents, among other results, the most extensive set of experimental results, compiled as of yet, on Type 2 puzzles.

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Sholomon, D., David, O. E., & Netanyahu, N. S. (2014). A generalized genetic algorithm-based solver for very large jigsaw puzzles of complex types. In Proceedings of the National Conference on Artificial Intelligence (Vol. 4, pp. 2839–2845). AI Access Foundation. https://doi.org/10.1609/aaai.v28i1.9148

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