Sub-dimension particle swarm optimization(s-dPSO) is proposed based on basic particle swarm optimization (bPSO). Each dimension of particle in s-dPSO is updated in turn. The dimensions with poor diversity would be mutated that is initialized again to improve the diversity of population and get global optimal solution when the algorithm is in the local convergence. Most Benchmark function get go...

In order to improve performance of particle swarm optimization algorithm (PSO) in global optimization, the reason of premature convergence of the PSO is analyzed, and a new particle swarm optimization based on two subswarms (TSS-PSO) is proposed in this paper. The particle swarm is divided into two identical sub-swarms, that is, the first sub-swarm adopts basic PSO model to evolve, whereas the ...

The particle swarm optimization technique is one of the promising tools to find a proper optimum for an unknown function optimization. Especially, global search capability of the method is very powerful. The particle swarm optimization utilizes common knowledge of the group and individual experiences effectively. That is, direction for the best estimator that a particle has ever reached, direct...

In order to overcome the weakness that particle swarm optimization algorithm is likely to fall into local minimum when the complex optimization problems are solved, a new adaptive dynamic particle swarm optimization algorithm is proposed. The paper introduces the evaluation index of particle swarm premature convergence to judge the state of particle swarm in the population space, for the sake o...

This paper presents four optimization algorithms: Bacterial Foraging Optimization (BFO), Particle Swarm Optimization (PSO), Chaos Particle Swarm Optimization (CPSO) and Bacterial Swarm Optimization (BSO), and a neural network compensator: Resource Allocation Network (RAN) to aircraft automatic landing control design. When wind disturbance is beyond the originally scheduled flight condition, the...

This paper assumes each user has more than one queue, derives a new packet-dependant proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new cross-layer packet-dependant OFDM scheduling schemes based on proportional fairness for heterogeneous classes of traffic. Scenario 1, scenario 2 and scenario 3 lead r...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

Combined the global optimization ability of particle swarm algorithm and memory capacity of tabu algorithm, this paper proposed an automatic vector road network matching method based on the combination of particle swarm optimization and tabu strategy. Firstly, the similarity between node entities is evaluated by means of geometric and topological characteristics. Then, the basic principle of gl...