Abstract: Abstract：Aiming at the problems in the optimization process of Archimedes optimization algorithm （AOA）， such as the weak ability of global exploration and local development， low optimization accuracy and easy to fall into local optimization， an Archimedes optimization algorithm based on LHS and sine-cosine search operator （LSAOA） is proposed. Firstly， Latin hypercube sampling method is used to initialize the population to improve the balance and diversity of the population； Secondly， the switching mode between global search and local search is changed to improve the convergence speed and accuracy of the algorithm； Finally， the sine-cosine search operator is introduced to improve the local search mode and improve the local search development ability of the algorithm. The simulation experiment compares lsaoa algorithm with other improved AOA algorithms and other meta heuristic algorithms under the international benchmark function. The experimental results show that lsaoa algorithm has better comprehensive performance in solving accuracy and convergence speed.

Key words: Key words： Archimedes optimization algorithm, Latin hypercube sampling, Sine-cosine search operator