Abstract—This article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for fixed order controller design. The major objective of the work is to compare the ability, computational effectiveness and efficiency to solve the optimization problem for both algorithms (PSO and GA). All simulation has been performed using a software program developed ...

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the appl...

Supply chain management (SCM) is a subject that has found so much attention among different commercial and industrial organizations due to competing environment of products. Therefore, integration of constituent element of this chain is a great deal. This paper proposes a multi objective production-allocation and distribution planning problem (PADPP) in a multi echelon supply chain network. We ...

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the appl...

One of the most important factors that affects construction costs of highways is the earthwork cost. On the other hand, the earthwork cost strongly depends on the design of vertical alignment or project line. In this study, at first, the problem of vertical alignment optimization was formulated. To this end, station, elevation and vertical curve length in case of each point of vertical intersec...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can ...

Text categorization and feature selection are two of the many text data mining problems. In text categorization, the document that contains a collection of text will be changed to the dataset format, the dataset that consists of features and class, words become features and categories of documents become class on this dataset. The number of features that too many can cause a decrease in perform...

This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and ...

There are many problems exist in the Evolutionary Algorithm (EA) using Genetic Algorithm (GA), such as slow convergence speed, being easy to fall into the partial optimum ,etc. Particle Swarm Optimization (PSO) can accelerate the space searching and reduce the number of convergences and iterations. The proposed characteristics of Genetic Algorithm Particle Swarm Optimization (GAPSO) are proved ...

Support vector machine (SVM) is a popular pattern classification method with many application areas. SVM shows its outstanding performance in high-dimensional data classification. In the process of classification, SVM kernel parameter setting during the SVM training procedure, along with the feature selection significantly influences the classification accuracy. This paper proposes two novel in...