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Multi-objective optimization problems with interval (MOPs-I) uncertainties parameters are common in practice. Evolutionary multi-objective (EMO) algorithms are popularly employed to solve these problems due to their powerful explorations. The comparison strategies among interval objectives of MOPs-I are crucially important for obtaining a superior Pareto front when applying EMOs. By effectively combining...
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...
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