Research on intelligent construction-oriented civil engineering construction resource scheduling and intelligent optimization algorithm

The traditional civil engineering management mode cannot meet the urgent demand of modern engineering projects for "high quality, low cost and short construction period" because of its dependence on manual experience, lagging information transmission and low efficiency of resource scheduling. As the product of the deep integration of building industrialization and informatization, intelligent construction provides the possibility to solve these problems. Based on the characteristics of civil engineering construction, this paper establishes a multi-objective optimization mathematical model, covering the objectives of time limit, cost and resource balance. Combining genetic algorithm (GA) and particle swarm optimization (PSO), an improved hybrid algorithm is proposed. Through case analysis and verification, the results show that the hybrid GA-PSO algorithm is the best in all indicators, with a total construction period of 106 days, a total cost of 109.2 million yuan, a resource volatility of 14% and a resource idle rate of 9%, which is obviously superior to the traditional critical path method (CPM) and the other two standard algorithms GA and PSO. Compared with the traditional CPM, the hybrid GA-PSO algorithm reduces the construction period by 29 days, reduces the cost by about 18%, and greatly reduces the resource volatility and idle rate, showing stronger optimization ability and higher efficiency. This research provides technical support for the digital transformation of civil engineering industry and helps to promote the development of smart cities, green buildings and other emerging fields.