Abstract
A parallel global optimization algorithm based on the density clustering technique by Boendeb is described. Two versions, the synchronous and the asynchronous one, are proposed and numerical experiments are carried out using a simulation environment of a parallel MIMD machine. A comparison between the sequential and parallel versions of the algorithm, both in term of time and of number of function evaluations, shows that the asynchronous one is very promising for machines based on MIMD architecture
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.
