In this paper, we study the use of particle swarm optimization (PSO) for a class of non-stationary environments. The dynamic problems studied in this work are restricted to one of the possible types of changes that can be produced over the fitness landscape. We propose a hybrid PSO approach (called HPSO dyn), which uses a dynamic macromutation operator whose aim is to maintain diversity. In ord...

In this paper, we address the problem of localizing sensor nodes in a static network, given that the positions of a few of them (denoted as “beacons“) are a priori known. We refer to this problem as “autolocalization.” Three localization techniques are considered: the two-stage maximum-likelihood (TSML) method; the plane intersection (PI) method; and the particle swarm optimization (PSO) algori...

AbstrAct This chapter presents a hybrid between a particle swarm optimization (PSO) approach and scatter search. The main motivation for developing this approach is to combine the high convergence rate of the PSO algorithm with a local search approach based on scatter search, in order to have the main advantages of these two types of techniques. We propose a new leader selection scheme for PSO,...

Network on Chip (NoC) architectures have emerged in recent years as scalable communication fabrics to enable high bandwidth data transfers in chip multiprocessors (CMPs). These interconnection architectures still need to conquer many challenges, e.g., significant power consumption and high data transfer latencies. Hybrid electro-photonic NoCs have been recently proposed as a solution to mitigat...

Stock market indices prediction is one of the most important issues in the financial field. Although many prediction models have been developed during the last decade, they suffer a poor performance because indices movement is highly non stationary and volatile dynamic process. As improving the prediction accuracy becomes an important issue, we propose a new hybrid genetic Algorithm / Particle ...

This paper presents a novel fuzzy particle swarm optimization with cross-mutated operation (FPSOCM), where a fuzzy logic system developed based on the knowledge of swarm intelligent is proposed to determine the inertia weight for the swarm movement of particle swarm optimization (PSO) and the control parameter of a newly introduced cross-mutated operation. Hence, the inertia weight of the PSO c...

The volume of digitized text documents on the web have been increasing rapidly. As there is huge collection of data on the web there is a need for grouping(clustering) the documents into clusters for speedy information retrieval. Clustering of documents is collection of documents into groups such that the documents within each group are similar to each other and not to documents of other groups...

In this paper, a new Hybrid Charged System Search and Particle Swarm Optimization, HCSSPSO, is presented. Although Particle Swarm Optimization (PSO) has many advantages, including directional search, it has also some disadvantages resulting in slow convergence rate and low performance. On the other hand, the Charged System Search (CSS) is a robust optimization algorithm which has been successfu...

This paper presents a hybrid particle swarm algorithm for solving the multiobjective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer se...

There is a tremendous proliferation in the amount of information available on the largest shared information source, the World Wide Web. Fast and high-quality document clustering algorithms play an important role in helping users to effectively navigate, summarize and organize the information. Recent studies have shown that partitional clustering algorithms are more suitable for clustering larg...