In view of the problem that Bloch Quantum Genetic Algorithm (BQGA) is easy to fall into local optimum. an improved BQGA is proposed. The algorithm can control the step size and the mutation probability in real time in the iterative process. avoiding over the optimal solution and guaranteeing search efficiency. https://parisnaturalfoodes.shop/product-category/fuchsia-flood-lipstick/
Application of Improved BQGA in Robot Kinematics Inverse Solution
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