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Browsing by Author "Yu, Chiung-Hsueh"

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    An efficient algorithm for solving nonograms
    (2011-08-01)
    Yu, Chiung-Hsueh
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    Lee, Hui-Lung
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    Chen, Ling-Hwei
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    資訊工程學系
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    Department of Computer Science
    Nonogram is one of logical games popular in Japan and Netherlands. Solving nonogram is a NP-complete problem. There are some related papers proposed. Some use genetic algorithm (GA), but the solution may get stuck in local optima. Some use depth first search (DFS) algorithm, the execution speed is very slow. In this paper, we propose a puzzle solving algorithm to treat these problems. Based on the fact that most of nonograms are compact and contiguous, some logical rules are deduced to paint some cells. Then, we use the chronological backtracking algorithm to solve those undetermined cells and logical rules to improve the search efficiently. Experimental results show that our algorithm can solve nonograms successfully, and the processing speed is significantly faster than that of DFS. Moreover, our method can determine that a nonogram has no solution.
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    SOLVING JAPANESE PUZZLES WITH LOGICAL RULES AND DEPTH FIRST SEARCH ALGORITHM
    (2009)
    Jing, Min-Quan
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    Yu, Chiung-Hsueh
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    Lee, Hui-Lung
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    Chen, Ling-Hwei
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    資訊工程學系
    Japanese puzzle is one of logical games popular in Japan and Netherlands. Solving Japanese puzzle is a NP-complete problem. There are some related papers proposed. Some use genetic algorithm (GA), but the solution may be wrong. Some use depth first search (DFS) algorithm, which is an exhaustive search, the execution speed is very slow. In this paper, we propose a puzzle solving algorithm to treat these problems. Based on the fact that most of Japanese puzzle are compact and contiguous, some logical rules are deduced to paint some cells. Then, the DFS algorithm with the "branch and bound" scheme, which is used to do early termination for those impossible paths, is used to solve those undetermined cells. Experimental results show that our algorithm can solve Japanese puzzles successfully, and the processing speed is significantly faster than that of DFS.