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It is critical for the construction party to meet the established economic and social demand for the construction project with the shortest construction period and the lowest cost. In this study, the construction characteristics of the project were analyzed. In addition, the multiconstraint and multitarget construction optimization model with minimum period and cost was established based on the quantum genetic algorithm. In order to improve the adaptability of the quantum genetic algorithm for the multiobjective model, the encoding form, quantum revolving door, and genetic flow of the algorithm were reconstructed. MATLAB 2016b was used as the simulation platform, and the implementation of the algorithm was improved according to the characteristics of the variables in the construction project, including period and cost. Finally, the optimization of the algorithm was verified and analyzed by an engineering example. The results showed that using the multiobjective quantum genetic algorithm, the optimal duration/cost can be achieved and the most reasonable and effective control decision scheme for the construction management can be provided through the Pareto solution set.

Purpose The construction industry is characterized by a long construction period, high cost and many uncontrollable factors. The owners and contractors are increasingly focusing on the efficiency of their construction and costs in pursuit of greater economic benefits. However, current methods used in the construction period and cost optimization analysis with multiple constraints the have their own limitations. Therefore, this study aims to propose a combination of genetic algorithm (GA) and building information modeling (BIM) to construct a five-dimensional construction duration-cost optimization model with the advantages of optimization and simulation for optimization. Design/methodology/approach This design first analyzed the characteristics of changing construction period and cost and then improved the genetic mechanism and the data processing method in the GA according to the aforementioned characteristics. Then, BIM technology was combined with GA to testify the feasibility of the model in the practical engineering project. Findings The result proved that this new method was reasonable and effective in dealing with the complicated problem of period and cost. GA accelerated the optimization process and yielded a reliable Pareto solution. BIM technology simulated the construction process before construction to increase the feasibility of the construction scheme. Originality/value This method not only can rapidly provide the best construction period/cost decision to the architect according to the previous working period/cost or contract data that can meet the demands of the architect but also visualize the construction and give a dynamic schedule of the project.