Concrete as the basic material of construction project, its proportioning directly affects the project quality and cost. In this paper, a multi-objective optimization model for concrete proportioning is constructed, and an improved multi-objective particle swarm algorithm (IMOPSO) is proposed with the clinker three-rate value deviation and raw material cost as the optimization objectives. The algorithm improves the convergence and diversity of the solution through a dual external archiving mechanism and a two-stage global optimal selection strategy. On the ZDT standard test function, the IMOPSO algorithm achieves a convergence degree of 0.00355, which is significantly better than the NSGA-II and SPEA2 algorithms. The algorithm is applied to the optimization of 7 groups of ratios in a concrete enterprise, and the results show that compared with the NSGA-II algorithm, the running time of IMOPSO is shortened from an average of 90.29 seconds to 28.31 seconds, with an efficiency improvement of 68.6%; the cost of raw materials can be as low as 511.54 yuan/ton under the premise of ensuring that the quality control indexes meet the requirements. The study shows that the improved algorithm has higher solution accuracy and efficiency in solving the concrete ratio optimization problem, which provides an effective tool for intelligent decision-making in concrete production.
