TY - GEN
T1 - A high performance algorithm for puzzle reconstruction problem
AU - Tsai, Chun Wei
AU - Tseng, Shih Pang
AU - Chiang, Ming Chao
AU - Yang, Chu Sing
PY - 2012/12/31
Y1 - 2012/12/31
N2 - Since a puzzle solver, for the puzzle reconstruction problem, can be applied to many other real world problems, various studies have focused on improving the end result of the puzzle solvers they proposed for several years. In spite of these efforts, the puzzle reconstruction problem, however, has never fully solved by using a search algorithm with a limited computation time. In this paper, and effective search algorithm is presented for the puzzle reconstruction problem. The proposed algorithm uses ant colony optimization to guide the search directions toward the global optimal solution, the color information to measure the similarity between pairs of puzzles, and an effective reconstruction strategy to improve the end result. To evaluate the performance of the proposed algorithm, we compare it with several state-of-the-art puzzle reconstruction algorithms. The simulations results show that the proposed algorithm out performs all the state-of-the-art algorithm we compared in this paper.
AB - Since a puzzle solver, for the puzzle reconstruction problem, can be applied to many other real world problems, various studies have focused on improving the end result of the puzzle solvers they proposed for several years. In spite of these efforts, the puzzle reconstruction problem, however, has never fully solved by using a search algorithm with a limited computation time. In this paper, and effective search algorithm is presented for the puzzle reconstruction problem. The proposed algorithm uses ant colony optimization to guide the search directions toward the global optimal solution, the color information to measure the similarity between pairs of puzzles, and an effective reconstruction strategy to improve the end result. To evaluate the performance of the proposed algorithm, we compare it with several state-of-the-art puzzle reconstruction algorithms. The simulations results show that the proposed algorithm out performs all the state-of-the-art algorithm we compared in this paper.
UR - http://www.scopus.com/inward/record.url?scp=84871565205&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84871565205&partnerID=8YFLogxK
U2 - 10.1109/ICMLC.2012.6359630
DO - 10.1109/ICMLC.2012.6359630
M3 - Conference contribution
AN - SCOPUS:84871565205
SN - 9781467314855
T3 - Proceedings - International Conference on Machine Learning and Cybernetics
SP - 1698
EP - 1703
BT - Proceedings of 2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012
T2 - 2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012
Y2 - 15 July 2012 through 17 July 2012
ER -