A Brief Survey of Honey Bee Mating Optimization Algorithm to Efficient Data Clustering

Background: In contemporary years Honey Bee mating Optimization algorithms have been extensively used as specific research and optimization tools in numerous domain that has critical issues related to Science, technology, commerce and Engineering. Due to the simple and flexible nature of the HBMO algorithm, it has been used in load profile clustering in present day situation. Objectives: This survey paper attempts to provide a comprehensive survey of research application of HBMO on load profile and elucidate the constraints and convergence properties of the algorithm and highlights its application in solving certain current issues by enhancing its approach with innovative changes that could be adopted within the context and requirement of the problem to be addressed. Through this survey paper It is shown that the Load profile clustering could be performed in an economical and efficient manner by applying HBMO algorithm with certain changes in time and length of metering and the results obtained through this method are quite promising and comparable well with the final results of the other approach.