基于蚁群算法的装配式建筑施工工序多目标优化模型

Multi Objective Optimization Model of Installation Process ofPrefabricated Buildings Based on Ant Colony Algorithm

作为我国经济支柱产业,建筑业长期以来属于粗放型产业。由于粗放式管理,建筑施工阶段往往面临工期延长、成本超标等问题,并产生大量碳排放。为了有效解决这一问题,本文从装配式建筑施工过程出发,首先以叠合板构件安装过程为例详细梳理了施工工序以及每道工序的人工、材料以及机械或设备等资源的消耗类型。随后,结合多目标优化思想,构建了施工工序多目标优化数学模型,并汇总分析了现场调研获取的施工数据,得出每道工序在不同执行模式下的成本、工期与碳排放。最后,利用蚁群算法寻找出使得“成本-工期-碳排放”综合最优的工序执行模式组合,并对优化结果进行相关分析,验证了本文多目标优化的可行性与合理性,从而能有效指导建筑施工过程的优化管理。

As a pillar industry of China s economy,the construction industry belongs to the extensive industry for a long time.Due to extensive management,the construction stage is often faced with problems such as prolonged construction period,cost overrun,and usually produces a lot of carbon emissions.In order to effectively solve this problem,starting from the construction process of prefabricated buildings,this paper takes the installation process of laminated plate members as an example,analyzing the construction process and consumption types of labor,materials,machinery or equipment in each construction process in detail.Then,combined with the idea of multi-objective optimization,this paper constructs the multi-objective optimization mathematical model of construction process,summarizes and analyzes the construction data obtained from field investigation so as to obtain the cost,construction period and carbon emission of each process under different execution modes.Finally,the ant colony algorithm is used to find out the process execution mode combination which makes the multi objective optimization of“cost-duration-carbon emissions”come true,at the same time,the correlation analysis of the optimization results verifies the feasibility and rationality of the multi-objective optimization in this paper so as to effectively guide the optimal management of the construction process.