On clarifying misconceptions when comparing variants of the Artificial Bee Colony Algorithm by offering a new implementation
Artificial Bee Colony (ABC) is a Swarm Intelligence algorithm that has obtained meta-heuristic researchers attention and favor over recent years. It comprises good balance between exploitation (employed bee phase and onlooker bee phase) and exploration (scout bee phase). As nowadays, more researchers are using ABC and its variants as a control group to perform comparisons, it is crucial that comparisons with other algorithms are fair. This paper points to some misapprehensions when comparing meta-heuristic algorithms based on iterations (generations or cycles) with special emphasis on ABC. We hope that through our findings this paper can be treated as a beacon to remind researchers to learn from these mistakes.
artificial bee colony algorithm swarm intelligence experiment replication