Lisha Liu

In this paper, a particle swarm optimizer that integrates self-organizing maps and k-means clustering (SK-PSO) is proposed. This optimizer generates an asymmetric Cartesian space from random joint configurations when addressing the inverse kinematics of manipulators, followed by K-means clustering applied to the Cartesian space. The resulting clusters are used to reduce the dimensionality of the corresponding joint space using Self-Organizing Maps (SOM). During the solving process, the target point’s clustering region is determined first, and then the joint space point closest to the target point is selected as the initial population for the particle swarm algorithm. The simulation results demonstrate the effectiveness of the SK-PSO algorithm. Given the inherent asymmetry among different algorithms in handling the problem, SK-PSO achieves an average fitness value that is 0.02–0.62 times better than five other algorithms, with an asymmetric solving time that is only 0.03–0.34 times that of the other algorithms. Therefore, compared to the other algorithms, the SK-PSO algorithm offers high accuracy, speed, and precision.

This paper presents a novel approach to optimizing Grover’s algorithm for addressing the routing problem in quantum wireless communication networks. We begin by conducting a comprehensive analysis of key quantum communication technologies, including quantum teleportation and quantum entanglement swapping, and subsequently construct a quantum wireless communication network model grounded in these principles. Building on this foundation, we design and implement a multi-level quantum wireless network information transmission mechanism, incorporating quantum channels for identity authentication to ensure secure communication. Focusing on the routing challenges in quantum wireless communication networks, we propose innovative applications and optimizations of Grover’s quantum search algorithm. Specifically, we introduce an improved algorithm that efficiently searches for routing paths with maximal metrics within a limited number of hops. This enhancement not only significantly increases routing efficiency but also mitigates the risk of quantum channel disconnection caused by the depletion of entangled quantum pairs, thereby improving the overall success rate of communication. Simulation and experimental results demonstrate that the proposed optimization algorithm substantially enhances the routing performance of quantum wireless communication networks while maintaining robust security measures. This study offers a new solution to the routing challenges in quantum wireless communication networks and significantly optimizes Grover’s algorithm, contributing to the development of more efficient and reliable quantum communication networks.