Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pat...

This research paper presents an adaptation of the cat swarm optimization (CSO) to solve the traveling salesman problem (TSP). This evolutionary algorithm appeared in 2007 by Chu and Tsai for optimization problems in the continuous case. To solve TSP, which is a discrete problem, we will describe the various operators and operations performed in two different modes of this algorithm, which is th...

This paper proposes a solution methodology for the design of optimal and stable digital infinite impulse response (IIR) band stop (BS) filter by employing modified cat swarm optimization (CSO) algorithm. The error surface of digital IIR filters is non linear and multimodal because of the presence of the denominator terms. Therefore, the traditional filter design methods usually got stuck in the...

in this paper, a new enhanced version of the particle swarm optimization (pso) is presented. an important modification is made by adding probabilistic functions into pso, and it is named probabilistic particle swarm optimization (ppso). since the variation of the velocity of particles in pso constitutes its search engine, it should provide two phases of optimization process which are: explorati...

In this paper, we present an enhanced parallel cat swarm optimization (EPCSO) method for solving numerical optimization problems. The parallel cat swarm optimization (PCSO) method is an optimization algorithm designed to solve numerical optimization problems under the conditions of a small population size and a few iteration numbers. The Taguchi method is widely used in the industry for optimiz...

An Artificial Neural Network (ANN) is an abstract representation of the biological nervous system which has the ability to solve many complex problems. The interesting attributes it exhibits makes an ANN capable of ―learning‖. ANN learning is achieved by training the neural network using a training algorithm. Aside from choosing a training algorithm to train ANNs, the ANN structure can also be ...

In this article, multiple-product PVRP with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. A mathematical formulation was provided for this problem. Each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. To solve the problem, two meta-heuristic methods...