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Particle Swarm Optimization (PSO) has proved to be an effective global optimization in recent years. However, PSO still suffers from the prematurity to local optima. In order to solve this disadvantage, researches have carried out by combination with other optimizers. In recent years, a local optimization called Extremal Optimization (EO) has been introduced into PSO and gain improvements. Although,...
The guidance and control for near space vehicles are subjected to multiple constraints. To actualize the goals of guidance and achieve the flight mission, a guidance method for near space vehicles under the consideration of multiple constraints is proposed in this paper. The guidance problem is decomposed into two subproblems, a trajectory planning subproblem and a trajectory tracking subproblem....
The minimum rectilinear Steiner tree (MRST) problem is an NP-hard problem, which is one of the fundamental issues in electronic design automation (EDA). Particle swarm optimization (PSO) has been proved to be an efficient intelligent algorithm for optimization designs. This paper presents an application of discrete particle swarm optimization (DPSO) for resolving MRST in VLSI routing and proposes...
The particle swarm optimization algorithm (PSO) has successfully been applied to many engineering optimization problems. However, the most of existing improved PSO algorithms work well only for small-scale problems on low-dimensional space. In this new self-adaptive PSO, a special function, which is defined in terms of the particle fitness, swarm size and the dimension size of solution space, is introduced...
The particle swarm optimization algorithm (PSO) has successfully been applied to many engineering optimization problems. However, most of the existing improved PSO algorithms work well only for small-scale problems. In this new self-adaptive PSO, a special function, which is defined in terms of the particle fitness and swarm size, is introduced to adjust the inertia weight adaptively. In a given generation,...
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