Fuzzy Algorithms: Applying Fuzzy Logic to the Golden Ratio Search to Find Solutions Faster

Applying the concept of fuzzy logic (an abstract version of Boolean logic) to well-known algorithms generates an abstract version (i.e., fuzzy algorithm) that often results in computational improvements. Precision may be reduced but counteracted by gaining computational efficiency. The trade-offs (e.g., small increase in space, loss of precision) for a variety of applications are deemed acceptable. The fuzzification of an algorithm can be accomplished using a simple three-step framework. Creating a new fuzzy algorithm goes beyond simply converting the data from raw data into fuzzy data by additionally converting the operators and concepts into their abstract equivalents. This paper demonstrates: (1) how to apply the general framework by developing a fuzzy algorithm for a simple linear search algorithm and (2) the success of this process through the development of the Fuzzy Golden Ratio Section Search.