Designing the fuzzy controllers by using evolutionary algorithms and reinforcement learning is an important subject to control the robots. In the present article, some methods to solve reinforcement fuzzy control problems are studied. All these methods have been established by combining Fuzzy-Q Learning with an optimization algorithm. These algorithms include the Ant colony, Bee Colony and Arti...

Swarm Intelligence is the part of Artificial Intelligence based on study of actions of individuals in various decentralized systems. The Bee Colony Optimization (BCO) metaheuristic has been introduced fairly recently as a new direction in the field of Swarm Intelligence. Artificial bees represent agents, which collaboratively solve complex combinatorial optimization problem. The chapter present...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

This paper presents a new approach for solving the Combined Heat and Economic Dispatch (CHPED) problem using an artificial bee colony algorithm (ABC). Artificial Bee Colony algorithm (ABC) is inspired by the foraging behavior of honey bee swarm, is a biological inspired optimization. It shows more effective than the other optimization algorithms. The performance of the proposed algorithm ABC is...

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...

Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effect...

In order to resolve the multi-parameter optimization problem of finite impulse response (FIR) digital filter design, a quantum bee colony algorithm (QBCA) is proposed. The proposed QBCA is a multi-dimensional search algorithm for optimization of real numbers, and uses mechanisms of quantum evolution to update the positions of different quantum bees. Computer simulations have showed that FIR dig...

Artificial bee colony (ABC) algorithm, one of the swarm intelligence algorithms, has been proposed for continuous optimization, inspired intelligent behaviors of real honey bee colony. For the optimization problems having binary structured solution space, the basic ABC algorithm should be modified because its basic version is proposed for solving continuous optimization problems. In this study,...

In this work, performance of the Artificial Bee Colony Algorithm which is a recently proposed algorithm, has been tested on fuzzy clustering. We applied the Artificial Bee Colony (ABC) Algorithm fuzzy clustering to classify different data sets; Cancer, Diabetes and Heart from UCI database, a collection of classification benchmark problems. The results indicate that the performance of Artificial...