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In this paper, we propose an (SAPSO) Self-Adaptive Particle Swarm Optimization algorithm to solve the base station positioning problem. This algorithm is used to minimize the distance between the base station and cluster head owing to maximizing the energy. Moreover, the proposed algorithm is compared with many other conventional algorithms such as Artificial Bee Colony-Dynamic Scout bee (ABC-DS) algorithm, Genetic algorithm (GA), Particle swarm optimization (PSO) and Firefly with Dual Update Process (FFDUP) algorithm. Also, empowering SAPSO helps to find the optimal location of the base station to conserve energy in a noteworthy manner to maximize the network lifetime and prolong network connectivity regarding minimizing distance, delay and maximizing the security, energy. Our simulation results demonstrate that the proposed SAPSO algorithm performs better than the other conventional

Base Station Positioning in Wireless Sensor Network to aid Cluster Head Selection Process