A Generalized Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles of Complex Types
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.
Keywords
Cite
@article{arxiv.1711.06768,
title = {A Generalized Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles of Complex Types},
author = {Dror Sholomon and Eli David and Nathan S. Netanyahu},
journal= {arXiv preprint arXiv:1711.06768},
year = {2017}
}