In recently years, due to its power global search ability, artificial bee colony (ABC) has been successfully applied in many real-world problems. But its shortcoming of slow convergence speed still constraints the further applications. In this paper, for further enhancing its merits and conquering this shortcoming, we propose three improved strategies into ABC algorithm. First, we introduce a new array to preserve some elites of population ever achieved. Based on this, the new updating equations are proposed in our paper. Finally, a new updating mechanism for scout bee is proposed to learn from the defined array for further accelerating the convergence rate of population. Compared with the compared modern evolutionary algorithms, experimental results verify our proposed algorithm achieve better performance especially on the accuracy and stability of solutions.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.