This paper investigates an optimization procedure for the design of a synchronous motor (SM) using a particle swarm optimization (PSO) procedure. The PSO is proposed to minimize the motor volume and to maximize the motor output power. The proposed procedure has two stages for motor design. In the first stage, the stator parameters are optimized while in the second stage, the field and damper wi...

This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these freero...

Swarm Intelligence is the global intelligent behaviour emerged from the interaction of groups of simple agents. The existing swarm intelligence research mainly refers to swarm intelligence optimization, which with ant colony optimization and particle swarm optimization as a representative. And the relevant research work focuses on the performance improvements of the optimization algorithm, whic...

We specify an “individual-based” continuous-timemodel for swarm aggregation in n-dimensional Euclidean space. We show that the swarm is completely stable, and the center of the swarm is stationary. Numerical simulations indicate that the individuals will form a stable and cohesive swarm, and under the attraction/repulsion function, the bound of the swarm size will increase as the number of indi...

This paper proposes a dynamic-context cooperative quantum-behaved particle swarm optimization algorithm. The proposed algorithm incorporates a new method for dynamically updating the context vector each time it completes a cooperation operation with other particles. We first explain how this leads to enhanced search ability and improved optimization over previous methods, and demonstrate this e...

In this paper, a new alignment method based on the particle swarm optimization (PSO) technique is presented. The PSO algorithm is used for locating the optimal coupling position with the highest optical power with three-degrees of freedom alignment. This algorithm gives an interesting results without a need to go thru the complex mathematical modeling of the alignment system. The proposed algor...

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...

Handwritten digit recognition is an important but very hard practical problem. This is a classification problem for which support vector machines are very successfully used. Determining optimal support vector machine is another hard optimization problem that involves tuning of the soft margin and kernel function parameters. For this optimization we adjusted recent swarm intelligence bat algorit...

The Set Covering Problem is a formal model for many practical optimization problems. It consists in finding a subset of columns in a zero/one matrix such that they cover all the rows of the matrix at a minimum cost. To solve the Set Covering Problem we will use a metaheuristic called Fireworks Algorithm (FWA) inspired by the fireworks explosion. Through the observation of the way that fireworks...