To achieve an optimal solution to the traveling sales problem, School of Automation (TSP), an improved wolf pack algorithm (IWPA) that addresses this problem through migration, summoning, and besiegement behavior is proposed. This proposal is based on a basic WPA concept. In this algorithm, it retains the division-work cooperative search characteristics of WPA, adds negative feedback to the algorithm, and sets adaptive parameters, which solves the disadvantages of slow convergence speed and low-dimensional search efficiency of WPA. Finally, the path planning simulation of the IWPA was performed and the proposed approach was compared with ant colony optimization and particle swarm optimization. The simulation results indicate that IWPA has specific advantages over similar algorithms regarding feasibility, convergence, and stability.