In software project management there are several problems to deal, one of those is the Software Project Scheduling Problem (SPSP). This problem requires to assign a set of resources to tasks for a given project, trying to decrease the duration and cost of the whole project. The workers and their skills are the main resources in the project. In this paper we present the SPSP as a combinatorial o...

Reconfigurable antenna arrays are often capable of radiating multiple patterns by modifying the excitation phases of the elements. In this paper a method based on Firefly Algorithm (FA) has been proposed to obtain dual radiation pattern from a concentric ring array of isotropic elements, by finding out two different combinations of states for the switches, which are assumed to be connected with...

Nature-inspired swarm metaheuristics become one of the most powerful methods for optimization. In discrete optimization, the efficiency of an algorithm depends on how it is adapted to the problem. This paper aims to provide a discretization of the Firefly Algorithm (FF) for the scheduling of a specific manufacturing system, which is the mono processors two-stage hybrid flow shop (HFS). This kin...

The speech signal enhancement is for obtain clean speech signal from noisy signal environment. For multimodal optimization we better to use natural-inspired algorithms. In this paper we use Firefly algorithmWe compare the firefly algorithm with particle swarm optimization technique (PSO). The proposed algorithm contains three important module techniques. Those are preprocessing module, optimiza...

This paper presents an efficient and reliable evolutionary based approach to solve the optimal power flow (OPF) problem in the presence of static synchronous series compensator (SSSC). The firefly algorithm (FFA) is developed by using principle of firefly swarm. The approach has been tested on IEEE 30bus system with and without SSSC. The results show that FFA algorithm with SSSC gives better pe...

A split quaternion learning algorithm for the training of nonlinear finite impulse response adaptive filters for the processing of three- and four-dimensional signals is proposed. The derivation takes into account the non-commutativity of the quaternion product, an aspect neglected in the derivation of the existing learning algorithms. It is shown that the additional information taken into acco...

In this work, firefly algorithm (FA) is used in training feed-forward neural networks (FNN) for classification purpose. In experiments, three well-known classification problems have been used to evaluate the performance of the proposed FA. The experimental results obtained by FA were compared with the results reported by artificial bee colony (ABC) algorithm and genetic algorithm (GA). Also, si...