Browsing by Author "Al-Zarrad, Mohammad Ammar"

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    Materials price risk mitigation in construction projects
    (University of Alabama Libraries, 2014) Al-Zarrad, Mohammad Ammar; Moynihan, Gary P.; University of Alabama Tuscaloosa
    Construction materials cost estimation is considered one of the most important tasks in the development of project budget. Using material hedging to mitigate the risk of material price volatility is a new concept for construction companies. This thesis matched material hedging with the fuel hedging application utilized by airlines. The weather hedging process was used as a precedent for material hedging application in the construction industry. This thesis developed a model to provide a step by step guidance to apply material hedging in the construction industry. Further, this thesis matched its model with the model presented by Macdonald (2013) and provided a lower level of detail to support actual implementation of material hedging. Future work in this area could be the investigation of material hedging cost to decide if the hedging application is feasible. Also, validity and reliability of the model presented by this thesis should be investigated.
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    Multi-criteria decision-making model to improve linear repetitive projects time-cost trade-off in uncertain environment
    (University of Alabama Libraries, 2018) Al-Zarrad, Mohammad Ammar; Moynihan, Gary P.; University of Alabama Tuscaloosa
    The Time-Cost Trade-Off (TCT) problem is essential to project scheduling. The risk in TCT is significant because of the uncertainty associated with the estimation of project cost and duration. TCT problem in Linear Repetitive Projects (LRP) is a more complicated issue because of their unique repetitive nature. To solve this problem, this research developed an integrated Multi-Criteria Decision-Making (MCDM) model. The objective of this model is to help project managers improve their decisions regarding Time-Cost Trade-Offs. Two case studies are used to verify and validate the MCDM model. To quantify the magnitude of improvement that the MCDM model presents comparing with other methods that have been used before, a statistical analysis was conducted. The statistical analysis shows that there is enough evidence to conclude that the difference between the results obtained from the MCDM model and the other approaches is significant. The present MCDM model could help generate a more reliable schedule and mitigate the risk of projects running over-budget or behind schedule. Further, this model is a powerful decision-making tool to help managers reduce uncertainties and improve the accuracy of Time-Cost Trade-Offs. The present MCDM model employed Fuzzy linguistic terms, which provide decision-makers with the opportunity to give their judgments as intervals comparing to fixed value judgments. In conclusion, the present MCDM model has high robustness, and it is an attractive alternative to solve the TCT problem in LRP.