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Many-objective optimization problems widely exist in real world. However, there is lack of effective solutions to solve this problem because they contain more than three conflicting objectives. Based on quantum particle swarm optimization algorithm, this paper presents an efficient many-objective particle swarm optimization algorithm. In this algorithm, an improved quantum update method is introduced...
In order to solve the problem of path planning in an environment with many terrains, we propose a method based on interval multi-objective Particle Swarm Optimization (PSO). First, the environment is modeled by the line partition method, and then, according to the distribution of the polygonal lines which form the robot path and taking the velocity's disturbance into consideration, robot's passing...
Odor source localization is very important in real-world applications. We studied the problem of odor source localization and presented a modified particle swarm optimization algorithm for odor source localization of multi-robot. The algorithm dynamically adjusts two learning factors in the velocity update equation based on the effect of wind on self-cognition and social cognition of a particle. In...
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