Multiobjective Optimization Management of Construction Engineering Based on Ant Colony Algorithm

Abstract

In order to solve the problems of extensive management, the construction stage often faces the extension of construction period, excessive cost, and large amount of carbon emission and this paper proposes a multiobjective optimization management method of construction engineering based on ant colony algorithm. Firstly, taking the installation process of laminated plate components as an example, this paper combs the construction process and the consumption types of labor, materials, machinery, or equipment in each process in detail. Then, combined with the idea of multiobjective optimization, the multiobjective optimization mathematical model of construction process is constructed, and the construction data obtained from field investigation are summarized and analyzed to obtain the cost, construction period, and carbon emission of each process under different execution modes. The experimental results show that the ant colony algorithm is used to find the comprehensive optimal process execution mode combination of “cost duration carbon emission.” After optimization, the installation cost of laminated plate components is reduced by 1.55%, the construction period is reduced by 3.52%, and the carbon emission is reduced by 7.36%. The feasibility and rationality of multiobjective optimization in this paper are verified by experiments, which can effectively guide the optimization management of construction process.