Artificial Bee Colony algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. This paper presents Bee Swarm Optimization intended to introduce chaotic sequences and psychology factor of emotion into the algorithm. We define two emotions Bees could have, positive and negative, and correspond to two reaction to perception respectively. For avoiding premature c...

This paper is based on swarm intelligence and chaotic dynamics for learning. We address this issue by considering the problem of path planning for mobile robots. Autonomous systems assume intelligent behavior with ability of dealing in complex and changing environments. Path planning problem, which can be studied as an optimization problem, seems to be of high importance for arising of intellig...

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...

Determination of optimum location for drilling a new well not only requires engineering judgments but also consumes excessive computational time. Additionally, availability of many physical constraints such as the well length, trajectory, and completion type and the numerous affecting parameters including, well type, well numbers, well-control variables prompt that the optimization approaches b...

In this paper we present a modification of artificial bee colony (ABC) algorithm for constrained optimization problems. In nature more than one onlooker bee goes to a promising food source reported by employed bee. Our proposed modification forms a mutant solution in onlooker phase using three onlookers. This approach obtains better results than the original artificial bee colony algorithm. Our...

optimal sitting and sizing of shunt capacitor banks at the distribution networks for the purpose of power quality improvement is drawn much attention of electric power utilities in the last decades. determining the optimal number, location and sizing of capacitor using bee colony optimization algorithm (bco) is being presented in this paper. the bco algorithm is a new population based meta-heur...

Design a new novel intelligence algorithm which is called as chaotic quantum bee colony optimization (CQBCO) for discrete optimization problem. The proposed CQBCO applies the chaotic theory to quantum bee colony optimization (QBCO), which is an effective discrete optimization algorithm. Then the proposed chaotic quantum bee colony algorithm is used to solve benchmark functions and optimization ...

This study adapted an improved algorithm based on Artifical Bee Colony Optimization. It is not possible to justify that all the rules generated by fuzzy based apriori algorithm produce optimum result. Thus optimization of the result generated was carried out by Fuzzy Apriori algorithm using Fuzzy Artifical Bee Colony Optimization (FABCO), it's worth noting that a significant findings were revea...

Research in software testing has experienced a significant growth in recent years. One topic of special interest is fault detection techniques to reduce human interference and detect maximum faults. Priority is given to these techniques so that only higher priority techniques should be used instead of using individual techniques of lower priority. Bee Colony Optimization based upon natural phen...