In order to improve the low convergence accuracy and premature in the basic particle swarm algorithm applicable to the traveling salesman problem,an improved adaptive hybrid annealing particle swarm(IAHAPSO)algorithm was proposed.The algorithm adopts the population dispersion-based adaptive adjustment of the inertia weight to guide the correct evolutionary direction of the population,applies the simulated annealing algorithm to update the population extreme value strategy so as to avoid the particle search falling into the local optimal solution,and introduces the genetic hybridization operator to increase the diversity of the population in the process of population development.Its feasibility and superiority in solution accuracy and efficiency are verified by three standard TSPLIB test sets,and its effectiveness is further verified by a four-axis cutting machine test system.
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