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...

Reconfigurable Manufacturing System (RMS) justifies the need of hour by combining the high throughput of dedicated manufacturing system with the flexibility of flexible manufacturing systems. At the heart of RMS lies the Reconfigurable Machine Tools which are capable of performing multiple operations in its existing configurations and can further be reconfigured into more configurations which m...

Dimensionality reduction is a major task in remote sensing images. Feature selection is applied for performing dimensionality reduction. It selects the spectral features(i.e. Bands) and find a feature subset that preserves the semantics of the hyperspectral image. Based on particle swarm optimization (PSO), this paper proposes multi-objective functions for selecting the spectral feature subsets...

In recent years, particle swarm optimization (PSO) proposed by Kennedy et al. has been widely used as a general approximate solution method for optimization problems. The authors proposed a revised PSO (rPSO) method incorporating the homomorphous mapping and the multiple stretching technique in order to cope with shortcomings of PSO and showed its efficiency for nonlinear programming problems. ...

This paper introduces a modified PSO, Non-dominated Sorting Particle Swarm Optimizer (NSPSO), for better multiobjective optimization. NSPSO extends the basic form of PSO by making a better use of particles’ personal bests and offspring for more effective nondomination comparisons. Instead of a single comparison between a particle’s personal best and its offspring, NSPSO compares all particles’ ...

Abstract With the increasingly complex structure of transmission system, impact power outage caused by faults in grid is becoming greater and greater. The shall cut off maintenance line equipment to ensure supply safety system. During period, how achieve safe low-cost main content control. Aiming at problem maintenance, a particle swarm optimization algorithm with goal minimum impact, economic ...

in this paper, a multi-objective method is used to optimize a heat recovery steam generator (hrsg). two objective functions have been used in the optimization, which are irreversibility and hrsg equivalent volume. the former expresses the exergetic efficiency and the latter demonstrates the cost of the hrsg. decision variables are geometric and operational parameters of the hrsg. the results of...

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...