Ekmekci, D.2024-09-292024-09-292019978-172811820-8https://doi.org/10.1109/SSD.2019.8893259https://hdl.handle.net/20.500.14619/925116th International Multi-Conference on Systems, Signals and Devices, SSD 2019 -- 21 March 2019 through 24 March 2019 -- Istanbul -- 154292Artificial Bee Colony (ABC) algorithm can be used for all kinds of optimization problems for which metaheuristic methods can be used, and it is observed to yield successful results in many applications for different kinds of optimization problems. Ant Colony Optimization (ACO) can successfully evaluate the correlations between solution parts through pheromone approach and ABC algorithm can spread across different regions of the solution space in searching process. In this study, a new hybrid method, developed to improve ABC's performance in terms of local search with pheromone method, is introduced. Proposed method is tested a set of benchmark problems. © 2019 IEEE.eninfo:eu-repo/semantics/closedAccessartificial bee colonyoptimizationswarm intelligenceConference Object10.1109/SSD.2019.88932592-s2.0-85075632340456N/A452