Right-of-Way Acquisition Duration Prediction Model for Highway Construction Projects

2012 ◽  
Vol 138 (4) ◽  
pp. 540-544 ◽  
Author(s):  
Imad Aleithawe ◽  
R. Ralph Sinno ◽  
William H. McAnally
2018 ◽  
Vol 162 ◽  
pp. 02035
Author(s):  
Bevian I. Al Hadithi

The highways sector is a prominent sector in any country’s economy because of its impact on the well-being and safety of its citizens. The transport sector has an impact on social improvement and investment in the nation on the illustration that allows access to markets, production, jobs, health and other social services.This study investigates the causes of delay of highway construction projects in Iraq, which is frequent occurrence. Data was collected using questionnaires which were distributed to the key project participants; contractors, owners and consultants. The data were analyzed using the Frequency index and Spearman‟s rank correlation. The top seven causes of project delays were observed to be political decisions and political realities, the economic crisis of the country, delays in materials test of and obtaining the results, delay in monthly payments of contractor, failure treatment of the delays when implementing the project, the effects of weather, rain and high temperatures, delay in activities during implementation. It is recommended to establish an appropriate number of laboratories and adopt the field laboratory mechanism for the external and remote screens. Owners should give special attention to pay progress payment to contractors on time. The competent contractor who has prior experience in implementing the high projects should be selected. The contractor must take into consideration the weather conditions when preparing the time plan necessary to implement the project. The project management should identify these reasons and deal with them quickly in order to reduce the total delay of the project.


2007 ◽  
Vol 42 (3) ◽  
pp. 545-563 ◽  
Author(s):  
Konstantina Gkritza ◽  
Kumares C. Sinha ◽  
Samuel Labi ◽  
Fred L. Mannering

2019 ◽  
Vol 11 (14) ◽  
pp. 3828 ◽  
Author(s):  
Jin ◽  
Kim ◽  
Hyun ◽  
Han

Decisions made in the early stages of construction projects significantly influence the costs incurred in subsequent stages. Therefore, such decisions must be based on the life-cycle cost (LCC), which includes the maintenance, repair, and replacement (MRR) costs in addition to construction costs. Furthermore, as uncertainty is inherent during the early stages, it must be considered in making predictions of the LCC more probabilistic. This study proposes a probabilistic LCC prediction model developed by applying the Monte Carlo simulation (MCS) to an LCC prediction model based on case-based reasoning (CBR) to support the decision-making process in the early stages of construction projects. The model was developed in two phases: first, two LCC prediction models were constructed using CBR and multiple-regression analysis. Through k-fold validation, one model with superior prediction performance was selected; second, a probabilistic LCC model was developed by applying the MCS to the selected model. The probabilistic LCC prediction model proposed in this study can generate probabilistic prediction results that consider the uncertainty of information available at the early stages of a project. Thus, it can enhance reliability in actual situations and be more useful for clients who support both construction and MRR costs, such as those in the public sector.


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