Abstract: Aiming at  the problems of low search efficiency and susceptibility  to  local optima in  particle swarm optimization algorithm for optimizing  complex engineering problems, we proposed  a house topology-based particle swarm optimization algorithm. By 
 proposing  a house topology and designing a position update strategy tailored to its characteristics, the algorithm improved the information transmission and communication methods of  particle swarm optimization algorithm, thereby enhancing the convergence rate and global optimization capability of the algorithm. The comparative experimental results on benchmark
 functions show that the optimization accuracy, convergence speed, and stability of the house topology-based particle swarm optimization algorithm are superior to the other  4 improved algorithms. The simulation results  on 3 real-world engineering optimization problems further validate the  effectiveness and practicality of the proposed algorithm.

Key words: house topology,  , particle swarm optimization algorithm, engineering optimization problem, benchmark function, simulation experiment