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Two-ray model is the basic line-of-sight propagation model for radio-wave propagation. Fermat's principle of Geometrical optics theory shows that the optical ray path is the minimum distance, which can make the propagation problem of radio-wave into the optimization problem of path function. Particle Swarm Optimization (PSO) with the characteristic of better searching optimization, was used to calculate...
In this paper, a new swarm intelligence algorithm called SIA for global optimization is proposed. Each individual in population is firstly projected onto the boundary of the search space in order to extend the region of the global search. Secondly, a probability of generating new individual is computed based on the function values of the individual, its corresponding boundary point and the best individual...
PAM (Partitioning Around Medoids) was one of the first k-medoids algorithms. It attempts to determine k partitions for n objects. In the parallel particle swarm optimization, the number of particle is generally not too much. Therefore, PAM is used to divide the swarm is a best choises. This can make not only the location of particles within the same sub-swarm be in the relative concentrative, but...
For the task scheduling problem in the heterogeneous grid environment, a security benefit function is constructed by considering the task scheduling demand for confidentiality, integrity and authenticity. Then, according to the history behavior of grid resource nodes, node's credibility dynamic evaluation method is proposed by using the weighted function. Based on these, a new grid task security scheduling...
In this paper, a hybrid PSO algorithm is proposed. The new algorithm uses a simulated annealing based weighted-sum method to perform local search. The local search mechanism prevents premature convergence, hence enhances the convergence ability to the true Pareto front. Meanwhile the multi-objective optimization problem is converted into the constrained optimization problem. For the converted problem,...
In this paper, a dynamical particle swarm algorithm with dimension mutation is proposed. First, we design a dynamically changing inertia weight based on the degree of both the particle diversity and the improvement of the best solutions in the successive generations. By using this inertia weight the algorithm can more easily keep the diversity of the population, improve the convergent speed. Second,...
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