Cuckoo search implementation in LabVIEW

Abstract

LabVIEW is one of the various programming platforms which is widely utilized by the researchers of fraternities form both industry and academia, due to its simple-to-use graphical programming environment and extra ordinary easy interface with the hardware. LabVIEW is equipped with various in-built toolkits to perform different measurement and control tasks. One of these tasks is solving an optimization problem which is often encountered by researchers from variety of fields viz. control engineering, civil design, machine design, digital signal processing, and economics etc. However, the standard LabVIEW package is equipped with only a single global optimization algorithm, i.e. Differential Evolution (DE) algorithm and there exists a need of other efficient global optimization techniques. This paper deals with same concern and an effort has been made to develop a widely established and practiced global meta-heuristic algorithm i.e. cuckoo search algorithm (CSA) in LabVIEW environment. To test the CSA implementation in LabVIEW environment, nine benchmark test functions have been used and a comparative study has been made with DE algorithm. It was found from the conducted studies that CSA was more efficient in solving optimization problems with better convergence rate and repeatability than DE.