Precast concrete component utilization for building projects has been considered to become the leading trend in construction industry around the world. The logistics costs for precast concrete elements have usually accounted for a large proportion in whole costs executing projects. According to previous studies of logistics cost optimization that have been focused on the costs of transportation and warehouse, however, other necessary costs have not been examined carefully as costs of purchase, management, installation. Therefore, this study provides the comprehensive model of logistics expenditures for precast concrete structures using the Activitybased costing method. Also, this study develops the ALO algorithm by combining with other algorithms as opposition-based learning, mutation and crossover strategy to optimize costs. The results of the comparison and evaluation have proved that the new hybrid algorithm has superior results compared to the grey wolf algorithm, the particle swarm optimization, the dragonfly - particle swarm algorithm (DA-PSO) in the problem of finding logistics costs for precast concrete structures.