摘要
钢材费用在装配式建筑预制构件材料成本中最高占比超过51%,是进行采购成本优化的关键部分。本文考虑钢材市场价格波动的影响,研究应用ABC-LSSVR方法,预测未来多期钢材价格;进而以采购成本最小化为目的,考虑资金使用成本、生产连续性、价格波动等制约因素,建立钢材多期联合采购模型,应用粒子群算法对模型进行求解,得出最优的钢材采购策略,从而降低采购成本。实证分析表明:对比目前业内现行的钢材采购方案,应用优化后的采购方案,使钢材单位采购成本节约了34.21元/吨。
The cost of steel accounts for more than 50%of the prefabricated building materials cost,which is a key part of the procurement cost optimization of the prefabricated component supplier.This article considers the impact of steel market price fluctuations,researches and applies the ABC-LSSVR method to predict the future multi-period steel prices;and further aims at minimizing procurement costs,taking into account constraints such as capital use costs,production continuity,and price fluctuations.Combined purchasing model,the particle swarm algorithm is used to solve the model,and a scientific steel purchasing strategy is obtained,thereby reducing the procurement cost.An empirical analysis of a large-scale prefabricated component production base in W City shows that compared with the current procurement schemes in the industry produce better economic benefits.
作者
陈伟
谢欣
王朝晖
CHEN Wei;XIE Xin;WANG Zhaohui(School of Civil Engineering and Architecture,Wuhan University of Technology,Wuhan 430070,China;Wuhan Sanmu Hesen Construction Co.,Ltd.Wuhan 430061,China)
出处
《建筑经济》
北大核心
2020年第6期92-99,共8页
Construction Economy
基金
武汉市城建科研项目“装配式建筑工程项目管理规范研究”(武城建[2018]14号)。