The Artificial Bee Colony (ABC) algorithm is one of most popular stochastic, swarm based algorithm proposed by Karaboga in 2005 inspired from the foraging behaviour of honey bees. ABC has been applied to solve several problems in various fields and also many researchers have attempted to improve ABC’s performance by making some modifications. This paper proposes a new variant of ABC algorithm b...

The Artificial Bee Colony (ABC) algorithm recently gained high popularity by providing a robust and efficient approach for solving continuous optimization problems. In order to apply ABC in discrete landscape, a binary version of artificial bee colony (BABC) algorithm is proposed in this manuscript. Unlike the original ABC algorithm, the proposed BABC represents a food source as a discrete bina...

Nowadays computers are used to solve a variety and multitude of complex problems facing in every sphere of peoples’ life. However, many of the problems are intractable in nature exact algorithm might need centuries to manage with formidable challenges. In such cases heuristic or in a broader sense meta-heuristic algorithms that find an approximate solution but have acceptable time and space com...

This paper presents artificial bee colony optimization for solving multi-area economic dispatch (MAED) problem with tie line constraints considering transmission losses, multiple fuels, valve-point loading and prohibited operating zones. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The effectiveness of the proposed algorithm...

One of the most important and evolutionarily conserved roles of sleep is the processing and consolidation of information acquired during wakefulness. In both insects and mammals, environmental and social stimuli can modify sleep physiology and behavior, yet relatively little is known about the specifics of the wake experiences and their relative contribution to experience-dependent modulation o...

In this paper an overview of the areas where the Bee Colony Optimization (BCO) and its variants are applied have been given. Bee System was identified by Sato and Hagiwara in 1997 and the Bee Colony Optimization (BCO) was identified by Lucic and Teodorovic in 2001. BCO has emerged as a specialized class of Swarm Intelligence with bees as agents. It is an emerging field for researchers in the fi...

Hygienic behaviour, an intranidal task performed by middle-aged worker bees is an important behavioural mechanism of resistance to disease and to attack by Varroa destructor, an ectoparasitic mite. We studied the effect of a colony’s genotypic composition on the expression of this behaviour among worker bees by creating normal age-structured colonies with different proportions of bees belonging...

In this paper a hybrid model called Particle Swarm Artificial Bee Colony algorithm (PSABC) has been proposed. The PSABC algorithm is a combination of Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithm. PSABC has been used in this context to optimize the fitness value of a population in ABC algorithm using Particle Swarm Optimization. PSABC could be used to optimize the ...

This paper describes the application of two recently developed metaheuristic algorithms known as fire fly algorithm (FFA) and artificial bees colony (ABC) optimization for the design of linear array of isotropic sources. We present two examples: one for broad side arrays and the other for steerable linear arrays. Three instances are presented under each category consisting of different numbers ...