Using extended Monte Carlo simulation method for the improvement of risk management: Consideration of relationships between uncertainties

Rezaie, Kamran; Amalnik, Mohsen Sadegh; Gereie, A.; Ostadi, Bakhtiar; Shakhseniaee, M.

doi:10.1016/j.amc.2007.02.038

Cited by 76 publications

(51 citation statements)

References 4 publications

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“…Through the calculation of information entropy, we know that H(R 1 |ε se ) = 0.4576, H(R 1 ε m f ) = 0.1586. Sensitivity indicators are available according to (14) and (15). Thus, η se = 0.1284, η m f = 0.6982.…”

Section: Engineering Application and Discussionmentioning

confidence: 99%

“…Risk assessment is an important part of risk management, which is a tool designed to support all aspects of decision-making from the beginning to the end of a process. Various risk assessment tools have been widely used in tunnel and underground engineering, including event tree analysis [6], fault tree analysis [7], probabilistic risk analysis [8,9], the analytical hierarchy process [10], multicriteria verbal analysis [11], Grey systems [12], Bayesian networks [13], fuzzy sets [14], and Monte Carlo simulations [15,16].…”

Section: Introductionmentioning

confidence: 99%

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Risk Assessment and Decision-Making under Uncertainty in Tunnel and Underground Engineering

Xia

Xiong

Dong

et al. 2017

Entropy

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Abstract:The impact of uncertainty on risk assessment and decision-making is increasingly being prioritized, especially for large geotechnical projects such as tunnels, where uncertainty is often the main source of risk. Epistemic uncertainty, which can be reduced, is the focus of attention. In this study, the existing entropy-risk decision model is first discussed and analyzed, and its deficiencies are improved upon and overcome. Then, this study addresses the fact that existing studies only consider parameter uncertainty and ignore the influence of the model uncertainty. Here, focus is on the issue of model uncertainty and differences in risk consciousness with different decision-makers. The utility theory is introduced in the model. Finally, a risk decision model is proposed based on the sensitivity analysis and the tolerance cost, which can improve decision-making efficiency. This research can provide guidance or reference for the evaluation and decision-making of complex systems engineering problems, and indicate a direction for further research of risk assessment and decision-making issues.

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Section: Engineering Application and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk Assessment and Decision-Making under Uncertainty in Tunnel and Underground Engineering

Xia

Xiong

Dong

et al. 2017

Entropy

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“…The DCF method is typically represented by the net present value (NPV) and the internal rate of return (IRR), which are useful in the assessment of a reasonable value in terms of the difference between the present value and the future cash flow value [15]. However, SPPs can be inaccurately assessed when using traditional evaluation methods due to the large size of a project, its long-term operation period, the risk characteristics according to the uncertainty of the contract complexity, varying degrees of management flexibility, and the financial structure [15,[17][18][19].…”

Section: Related Workmentioning

confidence: 99%

A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk

Kim

2018

Sustainability

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This paper focuses on an investment decision-making process for sustainable development based on the profitability impact factors for overseas projects. Investors prefer to use the discounted cash-flow method. Although this method is simple and straightforward, its critical weakness is its inability to reflect the factor volatility associated with the project evaluation. To overcome this weakness, the Value-at-Risk method is used to apply the volatility of the profitability impact factors, thereby reflecting the risks and establishing decision-making criteria for risk-averse investors. Risk-averse investors can lose relatively acceptable investment opportunities to risk-neutral or risk-amenable investors due to strict investment decision-making criteria. To overcome this problem, critical factors are selected through a Monte Carlo simulation and a sensitivity analysis, and solutions to the critical-factor problems are then found by using the Theory of Inventive Problem Solving and a business version of the Project Definition Rating Index. This study examines the process of recovering investment opportunities with projects that are investment feasible and that have been rejected when applying the criterion of the Value-at-Risk method. To do this, a probabilistic alternative approach is taken. To validate this methodology, the proposed framework for an improved decision-making process is demonstrated using two actual overseas projects of a Korean steel-making company.

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“…Within the risk management area, more specifically, within the area of decision-making in a risky environment and measurement of uncertainties and their influence on health, investment, production and psychology fields, studies by Ward and Chapman (2003), Dawson and Dawson (1998), Yen-Chuan Chen and Hwong-Wen (2007), Terje and Zio (2010), Rezaie et al (2007), Sassi et al (2006), Corotis (2008), Soung-Hie Kim and ByeongSeok Ahn (1997) and Montgomery et al (1986) stands out. In the environmental uncertainty context, according to Harrison (2003), despite the great importance of the environmental uncertainty concept for the organizations, not much attention has been given by researchers to the aspects regarding measurement and validation.…”

Section: Literature Reviewmentioning

confidence: 99%

Product development time performance: Investigating the uncertainties on product conceptualization phase and the influence on time to market

Barros¹,

Possamai²,

Valentina³

2012

Afr. J. Bus. Manage.

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This empirical study identifies the main uncertainties present in the conceptualization phase of a new product development and their effect on time to market. In a previous study, 15 senior project leaders involved in the development of new products at a home appliance industry in Brazil were interviewed. In the study, the main uncertainty factors experienced by the project team where of the concept generation phase of a new product, was identified. Aiming at validating the uncertainty factors identified in the previous research, and also at identifying their influence on the timing of new product development of other categories of products, a field research has been carried out involving the new product development (NPD) of three different organizations leaders in their segments in Brazil: the home appliance industry, the hermetic compressor industry and the plastic transformation industry in Brazil. In that second study, NPD project senior leaders were interviewed about projects already carried out, and about the influence of uncertainty factors on the development time of those projects. With the data collected in the second research, a forecast model to calculate the average time of project development up to the launching of the end product for the NPDs analyzed was developed.

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Using extended Monte Carlo simulation method for the improvement of risk management: Consideration of relationships between uncertainties

Cited by 76 publications

References 4 publications

Risk Assessment and Decision-Making under Uncertainty in Tunnel and Underground Engineering

Risk Assessment and Decision-Making under Uncertainty in Tunnel and Underground Engineering

A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk

Product development time performance: Investigating the uncertainties on product conceptualization phase and the influence on time to market

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