The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of...

Close range photogrammetry network design is referred to the process of placing a set of cameras in order to achieve photogrammetric tasks. The main objective of this paper is tried to find the best location of two/three camera stations. The genetic algorithm optimization and Particle Swarm Optimization are developed to determine the optimal camera stations for computing the three dimensional c...

In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...

Suitable solutions for multi-objective optimization problems are investigated as a set of solutions in the literature, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. The proposed algorithm in this paper is a hybrid of the particle swarm optimization algorithm [1] and a random search technique with quadratic approximation formula[2] n...

Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly ...

Orthogonal Frequency Division Multiplexing (OFDM) has the inherent properties of being robust to interference and frequency selective fading and is de facto the adopted multiplexing techniques for the 4 th generation wireless network systems. In wireless system, resources such as bandwidth and power are limited, intelligent allocation of these resources to users are crucial for delivering the b...

In this paper, we present an extension of the heuristic called “particle swarm optimization” (PSO) that is able to deal with multiobjective optimization problems. Our approach uses the concept of Pareto dominance to determine the flight direction of a particle and is based on the idea of having a set of subswarms instead of single particles. In each sub-swarm, a PSO algorithm is executed and, a...

Watermark perceptibility and robustness must be ensured in order to enhance the practicality of digital watermarking. Taking human visual system characteristics into account fully, a particle swarm optimization method based on multi-wavelet digital watermarking is proposed. It utilizes Sa4 multiwavelet to embed digital watermark, chooses intermediate frequency in embedding digital watermark ada...

This paper investigates the ability of a discrete particle swarm optimization algorithm (DPSO) to evolve solutions from infeasibility to feasibility for the Vehicle Routing Problem with Time Windows (VRPTW). The proposed algorithm incorporates some principles from multi-objective optimization to allow particles to conduct a dynamic trade-off between objectives in order to reach feasibility. The...

In this paper, multi-objective optimization of hard turning has been reported. A neural network model was developed in order to model the surface roughness and tool wear characteristics of hard turning when CBN tools are used. Objective is to obtain optimum process parameters, which satisfies given limit, tool wear and surface roughness values and maximizes the productivity at the same time. A ...