Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees’ swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behavio...

This paper describes the first application of the Bees Algorithm to optimization problems. The Bees Algorithm (BA) is a search procedure inspired by the way honey bees forage for food. The paper presents the results obtained showing the robust performance of the BA. The results of comparative studies of the Bees Algorithm against other various discrete and continuous optimization algorithms for...

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IM...

The Artificial Bee Colony (ABC) algorithm is a popular swarm based algorithm inspired by the intelligent foraging behavior of honey bees. In the past, many swarm intelligence based techniques were introduced and proved their effective performance in solving various optimization problems. The exploitation of food sources is performed by onlooker bees in accordance with a proportional selection s...

Scheduling tasks on computational grids is known as NPcomplete problem. Scheduling tasks in Grid computing, means assigning tasks to resources such that the time termination and average waiting time criteria and the number of required machines are optimized. Based on heuristic or meta-heuristic search have been proposed to obtain optimal solutions. The presented method tries to optimize all of ...

The Weighted Set Covering Problem is a formal model for many practical optimization problems. In this problem the goal is to choose a subset of columns of minimal cost covering every row. Here, we present a novel application of the Artificial Bee Colony algorithm to solve the Weighted Set Covering Problem. The Artificial Bee Colony algorithm is a recent Swarm Metaheuristic technique based on th...

Modelling the behavior of social insects has attracted much research recently. Although honey–bees exhibit many features that encourage their use as models for intelligent behavior, up to our knowledge, no attempt for using honey-bees as a basis for optimization has been made in the literature. Some of the features that distinguish honey–bees are division of labor, communication on the individu...

The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic techniqu...

Honey-bees are one of the most well studied social insects. They exhibit many features that distinguish their use as models for intelligent behavior. These features include division of labor, communication on the individual and group level, and cooperative behavior. In this paper, we present a unified model for the marriage in honey-bees within an optimization context. The model simulates the e...

Modelling the behavior of social insects has attracted much research recently. Although honey– bees exhibit many features that encourage their use as models for intelligent behavior, up to our knowledge, no attempt for using honey-bees as a basis for optimization has been made in the literature. Some of the features that distinguish honey–bees are division of labor, communication on the individ...