Development of Simulation Based Approaches for Cost Estimation and Effect Analysis in Industrial and Humanitarian projects, Including System Dynamic Model and Monte Carlo Simulation

Cost management has become an integral part of management fields these days and has acquired great weight in the sector of project management as well. For most beneficiaries in the industry and humanitarian field, the management of projects is synonymous with the management of cost that affects directly the funds they need to mobilize to deliver their scheme. This thesis deals with the development and validation of simulation-based methods in the industry and the humanitarian field. In addition, several novel methods of cost management have been proposed considering the complexity of different factors. In the industry field, construction projects are characterized by great uncertainty. Appropriate risk analysis techniques are required to estimate the adequate coverage level against the occurrence of extra costs to increase the progress of the project in the tenders. The project margin increases when an excessive provision leads to more comprehensive coverage of the risks. Also, an accurate estimation of the contingency reserve is a crucial subject in construction projects to reduce the risk of overruns’ costs to an acceptable level and ensure the competitiveness of the company’s bid. To achieve this goal, a Company’s traditional approach has been applied to a real railway project and then a stochastic Risk Mode and Effect Analysis (RMEA) methodology base on Monte Carlo Simulation compared with the outcome of the company’s traditional approach applied to the same project. Most of the contingency estimation methods are included problems of subjectivity, complex mathematical models, and inaccurate estimation. This research proposes a combination of the Risk Mode and Effect Analysis (RMEA) with Monte Carlo Simulation (MCS) to determine the amount of allocated contingency fund that overcomes other methods’ limitations. The output of the analysis is a cumulative distribution function that demonstrates a coverage level related to the contingency amount to control extra cost and reduce the amount of contingency in projects. The developed method is validated by applying a real construction project and the obtained results are compared with the outcomes’ of the company’s traditional approach, clearly demonstrate the potential and the benefits of the proposed methodology. The result of the proposed method allows the decision-makers to operate with a lower contingency amount and control extra expenses of projects. In addition, a Decision Support System (DSS) approach using Failure Mode Effect Analysis and Monte Carlo Simulation has been discussed in this chapter. Besides, in the humanitarian field, A System Dynamic (SD) model has been applied to a humanitarian project to study the impact of different levels of financial aid paid to beneficiaries for different impact factors and estimate financial aid variation. Natural and man-made disasters seem unpredictable every year, increasing a wide range of universal sufferers. Several people are affected by the direct outcomes of these disasters, and their life depends on disaster relief aid administered by humanitarian organizations. Recently, there has been renewed interest in cash distribution in the humanitarian sector during disaster relief to increase access of vulnerable people to supporting services such as health or education and develop their life’s condition while rising the efficiency of humanitarian organizations committed to the program. The research proposes a casual-loop and system dynamic model to assess multi aspects of related impact factors to provide optimal support of beneficiaries. The model provides a decision-making framework with a high-level overview of the interactions between the education and health aspects of the recipient’s life, provides a system dynamics analysis including interactions that could have led to improving the vulnerable people's condition life. This system dynamics approach can be used to study the significant factors on education and health aspects of refugee crises such as the case of Syrian refugees in Turkey. Reviewing the humanitarian management literature, a causal loop is developed to better understand the health and education variables and their interactions. Then a system dynamic model is proposed and validated by historical data of Syrian refugees in Turkey. The result of financial aid sensitivity shows that more financial aid from humanitarian organizations are significantly improved the general health of refugees and also it is caused higher attendance for children in schools. In addition, enhanced financial aid supports can lead to improving access to water and hygiene facilities and also building more schools for their children.