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This paper proposes an electric business centre location model solved by centre–decentre quantum particle swarm optimization (CDQPSO). Firstly, a location model is built taking real factors into accounts such as the cost of business centres and consumers, the competitive relationship between newly built and existing ones, and their service qualities. Secondly, in order to solve the location model, a CDQPSO algorithm is proposed by the combination of centralized–decentralized learning and the motion mode of the quantum bound state particle. Benchmark experiments on the proposed CDQPSO and existing PSO algorithms indicate that the proposed algorithm has better performance. Finally, CDQPSO is applied to solve the locations of business centres. Compared with the existing methods, the new-built business centre of our proposed method can provide consumers with higher transportation convenience and service quality. Moreover, the power company can reduce the construction cost of business centres and improve social benefits.

With the development of 5G and the Internet of Things (IoT), mobile terminals are widely used in various applications under multicast scenarios. However, due to the limited computation resources of mobile terminals, reducing the computation cost of members in group key distribution processes of dynamic groups has become an important issue. In this paper, we propose a computation-efficient group key distribution (CEGKD) protocol. First, an improved secret sharing scheme is proposed to construct faster encryption and decryption algorithms. Second, the tree structure of logical key hierarchy (LKH) is employed to implement a simple and effective key-numbering method. Theoretical analysis is given to prove that the proposed protocol meets forward security and backward security. In addition, the experiment results show that the computation cost of CEGKD on the member side is reduced by more than 85% compared with that of the LKH scheme.