Making a decision model in construction companies regarding to weather risk by statistical method

Abstract

The inclement weather has an effect on the building construction projects duration and cost of projects. It causes stoppage in the projects and makes delays. Most of the project managers have problem to estimate the projects duration properly regarding to uncertain conditions such as weather risks and so on. Due to many weather factors that affect projects duration the principal component analysis (PCA) is used to reduce unnecessary factors. Also the priority and the importance of determined factors are evaluated using and analytical network process (ANP). A time series ARIMA model is used to forecast weather variables which are determined by the PCA and ANP methods. The forecasted value of weather variables will be applied in the multiple non linear regression models to estimate the human resource productivity, supplier efficiency and material norm which affect on duration of the project. .Based on this situation a decision making model which is multiple non linear regression models is proposed to estimate the duration of each activity on conditioned with the human resources productivity, supplier efficiency and material norm. Finally a decision support system is proposed to help project managers to make an accurate estimation for each activity.