Over past few decades, families of algorithms based on the intelligent group behaviors of social creatures like ants, birds, fishes, and bacteria have been extensively studied and applied for computer-aided optimization. Recently there has been a surge of interest in developing algorithms for search, optimization, and communication by simulating different aspects of the social life of a very we...

Swarm intelligence systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. Particle swarm, Ant colony, Bee colony are examples of swarm intelligence. In the field of computer science and operations research, Artificial Bee Colony Algorithm (ABC) is an optimization algorithm based on the intelligent foraging behavio...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. Various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper, a new binary version of the ABC algorithm inspired by quantum computing calle...

for Graph 3-Coloring Iztok Fister Jr.,∗ Iztok Fister,† and Janez Brest‡ Abstract The Artificial Bee Colony (ABC) is the name of an optimization algorithm that was inspired by the intelligent behavior of a honey bee swarm. It is widely recognized as a quick, reliable, and efficient methods for solving optimization problems. This paper proposes a hybrid ABC (HABC) algorithm for graph 3-coloring, ...

Bee colony optimization (BCO) is one of the most recent algorithms in swarm intelligence that can be used in optimization problems this algorithm is based on the intelligent behavior of honey bees in foraging process. In this paper bee colony optimization is applied to solve the task scheduling problem which tasks have dependency with each other. Scheduling of tasks that represents by directed ...

Honey bee colonies depend on pollen and nectar from flowers for their feed. The act of searching this by the bees is called foraging. foraging behaviour depends profitability sources as well needs colony. This modeled into an algorithm Foraging Bee Optimization Algorithm (FBA). After initialization, loops through three phases based bees’ nature 3W: Waggle, Work, Withdraw. A large number are ini...

In recent years several bee inspired optimization techniques have been proposed. These methods are either based on the bees’ foraging or mating behavior. Both foraging and mating regulate distributions outside (foraging) or within a colony (mating). Foraging determines the ratio of individuals that explore the surroundings for new food sources and those that exploit known food sources, while ma...