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A novel method of interpretive structural modeling (ISM) using a DNA-based algorithm is proposed in this paper. ISM is commonly used when the current technology and its application to business administration, industrial and systems engineering, organizational behavior, etc., concern complicated or problematic issues, or situations among an element set of the given problem context for making decisions. When structuring a problem with a large number of elements in an ISM process, the crossings among elements should be minimized. This computationally complex minimization is NP-complete. The proposed algorithm describes how to calculate complex relations among elements to create a hierarchically restructured digraph. This paper also presents a new approach for applying a biological method to ISM to measure the efficiency of the algorithm in calculating a large number of elements for decision making.