Research On Multi-objective Optimization Of Low Carbon Construction Machinery Configuration In Prefabricated Buildings

In recent years,prefabricated and other new building industrialization technologies have effectively promoted the process of fine management and emission reduction and carbon reduction in green construction in the building construction stage.The goal of comprehensively controlling project duration,cost and carbon emission in the construction stage has significant correlation with scientific mechanical configuration scheme.At present,the research on optimization of construction machinery configuration mainly focuses on railway,highway,bridge and other linear engineering projects,and low carbon target is not considered enough.Taking prefabricated buildings as the object,this paper studies the multi-objective optimization of mechanical configuration in the construction stage of prefabricated buildings.While taking into account the project duration and cost objectives,it fully implements the concept of low-carbon construction,which conforms to the development trend of realizing "low-carbon" goals in the current construction industry.Firstly,this paper constructs an optimization model of low-carbon construction machinery configuration for prefabricated buildings.Based on the existing theories of prefabricated building construction machinery selection,multi-objective optimization and low-carbon construction,this paper divides the normal operation time and slow operation time of machinery to accurately calculate the construction carbon emission.The concept of carbon tax is introduced to transform objects in the form of "carbon cost",and the number of machinery and equipment is selected as the decision variable.A multi-objective optimization model with minimization of "duration-cost-carbon emission" was established.Secondly,the QPSO algorithm is improved by introducing Levy flight mechanism.According to the step size and scale parameters of Levy distribution random search strategy,the particle position updating formula of QPSO algorithm is improved,and the coding design in line with engineering characteristics is proposed,so as to make up for the deficiency that particles cannot jump out of the local optimal and can not effectively obtain the global optimization results in the late running of QPSO algorithm.The performance test of the algorithm is conducted by combining five standard functions.It is found that the search ability and solving efficiency of the improved algorithm are significantly improved.Finally,a PC hanging plate hoisting project for the external wall of a prefabricated high-rise building is selected as an engineering case to verify the application and model and algorithm.According to the actual use of engineering machinery,648 kinds of construction machinery configuration schemes are set up in this paper,and the multi-objective optimization model is solved by the above algorithm.On this basis,the multi-objective optimization scheme and the single objective scheme,as well as the dual objective model only considering "duration-cost" were compared and analyzed.The results show that the duration,cost and carbon emission of the multi-objective optimization scheme are much lower than the original scheme,and the multi-objective optimization model with carbon constraints has significantly better control over the cost than the single objective and dual objective schemes,and the comprehensive optimization effect is outstanding.It can provide practical and effective solutions for multi-objective optimization of low-carbon construction machinery configuration in prefabricated buildings.The main contribution of this study is that,compared with the existing research on the configuration optimization of traditional construction machinery,this study focuses on prefabricated buildings,focuses on the construction of a multi-objective optimization model of mechanical configuration with "low-carbon" objectives,expands the scope of application of the model,and sets a large number of configuration schemes and solving algorithms matching the actual requirements of construction,further improving the feasibility of the optimization results.