Comparative Study: Defuzzification Functions and Their Effect on the Performance of the OFNbee Optimization Algorithm

Abstract

This article explores the pivotal role of defuzzification functions in the operation of the OFNBee algorithm, which employs ordered fuzzy number arithmetic to harness the inherent dynamics within a hive. Defuzzification functions serve the purpose of representing the OFN (Ordered Fuzzy Number) as a real number, while fuzzification functions convert real numbers into OFN representations. By focusing on the defuzzification function, this study investigates its impact on the performance of the OFNBee algorithm. The research demonstrates that tailoring dedicated fuzzification functions for specific optimization problems can yield substantial improvements in algorithmic performance. It is important to note that the overall performance of the algorithm relies on both the fuzzification and defuzzification functions. Consequently, this article provides valuable insights into the effects of the defuzzification function on algorithmic outcomes.