The Study Of Locations Facilities With Dynamic Demand In C Company

The site selection decision refers to selecting one or several locations from multiple locations as the construction site before investing in fixed assets,and hoping that the construction of this location can bring the best positive impact on subsequent benefits.Since the world’s advanced economies started monetary easing in 2014,global land prices have been rising,but demand has shown dramatic volatility.As a platform company for urban investment and construction,Company C has a large amount of fixed asset investment.Affected by the general environment,the company’s many projects in recent years have seen major changes in the environment when the project was initiated and the environment when the project was completed,resulting in project losses and pressure The increase in debt caused by cash flow has considerable financial risks.According to wind statistics,as of the end of 2018,the total amount of urban investment bonds was about 8 trillion yuan,and the proportion of urban investment bonds in the total debt of government platform enterprises was only a small part.According to the requirement of no more than 40% of net assets,the total debt scale It’s a pretty big number.The risks of urban investment in fixed assets are increasing.This article first uses the commonly used network location model in the facility location problem for basic modeling.The model will optimize the best construction point among all the available construction points.Secondly,this paper uses the infectious disease SIR model to transform the hypothetical demand in the network location problem into a dynamic demand function,and establishes the problem into a model group,and obtains the dynamic demand value by solving the SIR equation group.Finally,this paper uses the robust optimization model to conservatively optimize the relevant location parameters that may have changes.Robust optimization refers to the use of a series of mathematical methods to make the mathematical model achieve the optimal output of the result when the known data has a certain degree of uncertainty,which can prevent the error of the data from bringing significant changes to the result.Robust optimization is a more conservative solution,which usually achieves maximum allocation of resources under sub-optimal results.