Based on lean construction theory, this paper divides the total goal of high-quality residential intelligent construction work into four sub-goals: schedule, cost, quality and greenness, and establishes a multi-objective balanced optimization schedule model. The cost model is constructed by work decomposition method, the quality model is established based on construction reliability theory, and the greenness evaluation index system and model are established by synthesizing authoritative green building and assembly building evaluation system. On this basis, the crossover and mutation mechanisms in the immune genetic algorithm are introduced into the particle swarm algorithm to form the immune particle swarm genetic algorithm. Then the immune particle swarm genetic algorithm is used to solve the optimization model. The solution results show that the optimal equilibrium solution optimizes 12.12%, 16.55%, 5.56%, 5.00% in the level of schedule, cost, quality and environment, respectively, which effectively promotes the improvement of the overall construction objectives. The multi-objective modeling and optimization method proposed in this paper provides a reference for the management and decision-making of high-quality residential intelligent construction projects.
