Rough set methods are often used to reduce decision rules. Specific techniques using rough sets are used as a method for extracting decision rules. However, when dealing with many decision rules, the computational load becomes an issue. The problem of calculating all minimum-length decision rules is a NP-hard problem with combinatorial explosion. To address this computational challenge, this article describes a method to introduce biocomputing technology. This method applies DNA molecular technology to the reduction of decision rules, and can effectively reduce the computational complexity of the problem. Since L.M. Adleman pioneered the concept of the biological computing paradigm in 1998, this technology has provided the ability to develop new problem-solving algorithms by utilizing and implementing them in existing algorithms. However, algorithms using interdisciplinary DNA molecular technology for industrial engineering decision-making problems are still limited to areas where DNA is used in a limited way, and it cannot be said that they are widely used as a computational technology. This article describes the mechanisms and techniques of molecular engineering that manipulate DNA molecular structures and properties, and introduces the use of general molecular algorithms. In particular, we describe an algorithm we developed to minimize decision rules for minimum rule searches of rough sets.