Abstract
The artificial bee colony (ABC) is a well-studied algorithm developed to solve continuous function optimization problems by Karboga and Akay in 2009. ABC has been proven to be more effective than other biological-inspired algorithms with good exploration. However, ABC suffers from low exploitation and slow convergence in some cases. The ABC algorithm study has risen significantly over the past decade, with many researchers trying to improve ABC performance and apply it to solve problems. One method to enhance ABC is to borrow exploration technique from other algorithms. Researchers use pheromone, which is a technique used by Ant Colony optimization algorithm, to enhance ABC and addressed several aspects of using a pheromone to enhance the ABC. This systematic review aims to review and analysis articles about using pheromone to enhance ABC. Articles on related topics were systematically searched in four major databases namely Scopus, Web of Science, Association for Computing Machinery ACM and Google Scholar. To ensure that all research articles were considered the start date is not restrictions the search carry out till February 2021.Five articles were selected based on our inclusion and exclusion criteria for the systematic review. The results show that the use Pheromone to enhance ABC can increase the ABC exploitation ability and overcoming the late convergence. This paper also illustrates several potential pheromone using for future work.
Highlights
The artificial bee colony (ABC) algorithm is a well-studied algorithm developed to handle continuous function optimization issues by Karboga and Akay in 2005 [1]
ABC successfully used in many fields like Management of energy for mobile devices [2], [3] and for routing of Mobile Agents on IoT [4], [5]
The results reveal that using pheromone to enhance ABC is different in main three aspects
Summary
The artificial bee colony (ABC) algorithm is a well-studied algorithm developed to handle continuous function optimization issues by Karboga and Akay in 2005 [1]. It mimics the foraging behaviors of a swarm of bees to find food. Employed bee’s exploration for food sources and share the knowledge with an onlooker bee. Using the knowledge given down from the employed bee, the onlooker bee seeks to identify a better food source in the neighborhood. A scout bee and randomly seek for a new food source. In ABC, the exploitation is accomplished by both onlooker and employed bees, while the exploration process control by scout bees
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