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 ...

A Modified Artificial Bee Colony (ABC) algorithm for Economic Dispatch (ED) problem has been proposed. The Artificial Bee Colony (ABC) algorithm which is inspired by the foraging behavior of honey bee swarm gives a solution procedure for solving economic dispatch problem. It provides solution more effective than Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant Colony Optimizati...

Artificial bee colony algorithm simulating the intelligent foraging behavior of honey bee swarms is one of the most popular swarm based optimization algorithms. It has been introduced in 2005 and applied in several fields to solve different problems up to date. In this paper, an artificial bee colony algorithm, called as Artificial Bee Colony Programming (ABCP), is described for the first time ...

Although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreo...

In this paper we present a new, non-pheromone-based algorithm inspired by the behaviour of bees. The algorithm combines both recruitment and navigation strategies. We investigate whether this new algorithm outperforms pheromone-based algorithms, inspired by the behaviour of ants, in the task of foraging. From our experiments, we conclude that (i) the bee-inspired algorithm is significantly more...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Researchers used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron ...

An amplitude-optimised bit-edge equalisation (BEE) scheme is presented and compared with pulse-width modulation for mitigating intersymbol interference in high-speed backplane applications. With transmitter pre-coding and pre-emphasis, this BEE uses an adaptive LMS algorithm as a receiver error convergence engine by adjusting error derivation points. The optimality of the proposed BEE scheme is...

Graph Coloring, one of the most challenging combinatorial problems, finds applicability in many real-world tasks. In this work we have developed a new artificial bee colony algorithm (called O-BEE-COL) for solving this problem. The special features of the proposed algorithm are (i) a SmartSwap mutation operator, (ii) an optimized GPX operator, and (iii) a temperature mechanism. Various studies ...

The artificial bee colony (ABC) algorithm is an evolutionary optimization based on swarm intelligence and inspired by the honey bees’ food search behavior. Since ABC has been developed to achieve optimal solutions searching in continuous space, modification required apply it binary problems. In this study, we modify solve problems name improved (IbinABC). proposed method consists of update mech...