价格不确定下并行工程项目的原材料采购策略研究

发布时间：2018-04-24 01:40

本文选题：预制工程 + 库存管理　；参考：《武汉大学》2017年硕士论文

【摘要】：工程项目中,根据项目预算计划,建筑公司需要花费大量的资金购买建筑材料。因此,在合适的时间购买合适批量的原材料对建筑公司而言意义重大。相比于现浇混凝土工程项目,预制混凝土构件的应用能够缩短工程周期、改变材料成本组合和减少人工成本,预制构件正在上海等地区被广泛运用,预制工程项目原材料采购也由此引起研究者关注。预制件工程项目的主要建筑原材料包括预制构件、钢材、混凝土等,预制构件的制作也耗费一定比例的钢材。由于混凝土等材料价格相对稳定,而钢材的市场价格却是剧烈波动的,而本文由此背景出发,通过预测钢材的市场价格,并将预测的价格应用于项目的原材料采购中,使建筑公司在合适的时间购买合适批量的原材料,从而节约成本。文章首先选取了2015年11月到2016年11月钢材每日的价格为样本,并分别采用了时间序列模型、线性回归模型以及二者的组合模型对钢材的价格进行预测,组合模型是二者按照一定的权重进行组合而来。时间序列建模的具体过程是经过异常值观测、平稳性检验、纯随机性检验和季节性分析处理后得出了钢材价格的ARIMA(1,1,1),然后利用价格预测模型得出了钢铁的预测价格。线性回归模型是基于钢材价格可由线性趋势表示,而模型中价格变化斜率也能表示其钢材价格变化的快慢。文章再构建了结合原材料采购成本、人工成本和融资成本的采购模型,同时再将预测的钢材价格应用到采购模型中,最后分别探讨了在价格变化斜率、融资利率以及项目预制率改变的情况下,项目采购策略的最优性。为了验证结合价格预测和采购模型的有效性,文章以上海某建筑公司的并行工程项目为案例,结合项目的实际数据资料,从实证的角度分析了预测和采购模型的重要作用。研究结果表明,在项目的几个参数发生变化的情况下,该模型的最优采购策略总成本比标杆策略总成本都小。由此,结合预测技术和采购技术可以解决价格不确定性条件下的并行工程项目的原材料采购问题,这能为建筑企业订购原材料提供参考。
[Abstract]:According to the project budget, construction companies spend a lot of money on building materials. So buying the right batch of raw materials at the right time means a lot to the construction company. Compared with cast-in-place concrete projects, the application of precast concrete members can shorten the project cycle, change the material cost combination and reduce the labor cost. Prefabricated members are widely used in Shanghai and other areas. The procurement of raw materials for prefabricated projects has also attracted the attention of researchers. The main building raw materials of preform engineering project include prefabricated components, steel, concrete and so on. The production of prefabricated components also consumes a certain proportion of steel. Because the price of concrete and other materials is relatively stable, but the market price of steel is fluctuating violently, this paper, based on this background, forecasts the market price of steel, and applies the predicted price to the purchase of raw materials for the project. Cost savings by enabling the construction company to buy the right batch of raw materials at the right time. Firstly, the daily price of steel from November 2015 to November 2016 is selected as the sample, and the time series model, the linear regression model and the combination model are used to predict the steel price. The combination model is a combination of the two according to a certain weight. The concrete process of time series modeling is to get the price of steel by using the observation of outliers, the test of stationarity, the test of pure randomness and the processing of seasonal analysis. Then, the predicted price of iron and steel is obtained by using the price forecasting model. The linear regression model is based on the fact that the steel price can be expressed by the linear trend, and the slope of the price change in the model can also indicate the speed of the change of the steel price. At the same time, the predicted steel price is applied to the purchasing model. Finally, the slope of price change is discussed. When the financing rate and prefabrication rate change, the project procurement strategy is optimal. In order to verify the validity of combining price forecasting and purchasing model, this paper takes the concurrent engineering project of a construction company in Shanghai as an example, and analyzes the important role of forecasting and purchasing model from the perspective of demonstration. The results show that the total cost of optimal purchasing strategy is lower than that of benchmarking strategy when several parameters of the project are changed. Therefore, combining forecasting technology with purchasing technology can solve the problem of purchasing raw materials for concurrent engineering projects under the condition of price uncertainty, which can provide a reference for construction enterprises to order raw materials.
【学位授予单位】：武汉大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F274;F426.92

【参考文献】