Recent advances in particle swarm Page 1 Recent Advances in Particle Swarm **aohui Hu
Yuhui Shi Russ Eberhart Department of Biomedical Engineering EDS Embeded Systems …

A number of modern metaheuristic optimization techniques are being exploited to work out a
single-objective economic dispatch (ED) problem. The dispatch problems even become …

The ε constrained method is an algorithm transformation method, which can convert
algorithms for unconstrained problems to algorithms for constrained problems using the ε …

Particle swarm optimization (PSO) has received increased attention in many research fields
recently. This paper presents a comprehensive coverage of different PSO applications in …

This paper presents an improved particle swarm optimizer (PSO) for solving mechanical
design optimization problems involving problem-specific constraints and mixed variables …

Particle swarm optimization (PSO) is a novel metaheuristic inspired by the flocking behavior
of birds. The applications of PSO to scheduling problems are extremely few. In this paper …

In this correspondence, an approach based on coevolutionary particle swarm optimization to
solve constrained optimization problems formulated as min-max problems is presented. In …

Hardware variance can significantly degrade the positional accuracy of RSS-based WiFi
localization systems. Although manual adjustment can reduce positional error, this solution …

Constrained optimization problems are very important and frequently appear in the real
world. The/spl alpha/constrained method is a new transformation method for constrained …

Pattern recognition has as its objective to classify objects into different categories and
classes. It is a fundamental component of artificial intelligence and computer vision. This …