Abstract
A universal tabu search algorithm for the optimization of functions with continuous variables is presented based on the tabu method so far used, Essentially, the improvements include the transition criterion for different states, the determination of the step vector, the cancellation of tabu list, the stop criteria, and the restart from the optimum, etc. The numerical performances of the present algorithm are investigated using a benchmark problem and the geometry optimization of the multisection arc pole shoe in large salient pole synchronous generators.
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.
