Honey Bees Inspired Optimization Method: The Bees Algorithm

Baris Yuce, Michael S Packianather, Ernesto Mastrocinque, Duc Truong Pham, Alfredo Lambiase

    Research output: Contribution to journalArticlepeer-review

    110 Citations (Scopus)
    54 Downloads (Pure)


    Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

    Original languageEnglish
    Pages (from-to)646-662
    Number of pages17
    Issue number4
    Publication statusPublished - 6 Nov 2013


    • honey bee
    • foraging behavior
    • waggle dance
    • bees algorithm
    • swarm intelligence
    • Swarm-based Optimization
    • Adaptive neighbourhood search
    • site abandonment
    • random search


    Dive into the research topics of 'Honey Bees Inspired Optimization Method: The Bees Algorithm'. Together they form a unique fingerprint.

    Cite this