Abstract
This paper presents a hybrid nature inspired metaheuristic algorithms, which derive from Invasive Weed Optimization (IWO) and Cuckoo Search (CS). Based on the novel and distinct qualifications of IWO and CS, we introduce a hybrid IWO algorithm and try to combine their excellent features in this extended algorithm. The efficiency of this algorithm both in the case of speed of convergence and optimality of the results are compared with IWO algorithm through a number of common multi-dimensional benchmark functions. Finally, experimental results show that the proposed approach can be successfully employed as a fast and global optimization method for a variety of theoretical or practical purposes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
