Multi-objective construction machinery group configuration optimization based on improved particle swarm optimization algorithm

The construction of earthwork and stonework in the roadbed base is an indispensable part of the highway engineering construction process, and the reasonable allocation of engineering machinery groups has a significant impact on the cost and duration of the roadbed base construction. To solve the optimization problem of highway construction scheduling, a construction machinery group configuration optimization model with the goal of minimum cost and minimum construction period is established. An improved particle swarm algorithm with optimized particle swarm bounding search strategy is proposed and solved. Firstly, a equipment construction model is established. Then, a particle swarm bounding search strategy is constructed based on the Grey Wolf algorithm to dynamically adjust the composition of the particle swarm, improve the initial population quality, and integrate the Grey Wolf algorithm strategy into the particle swarm algorithm to improve the population diversity in the later stage of the algorithm and retain high-quality individuals during the evolution process. Finally, the effectiveness of the improved algorithm is verified by comparing the configuration example of the construction machinery group with the algorithm