Monte Carlo approach to fuzzy AHP risk analysis in renewable energy construction projects

Project management body of knowledge (PMBOK) Uncertainty Mixed qualitative and quantitative risk assessment approach Mathematics Probability theory Engineering Industrial engineering BusinessThis study presented a qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions. Accordingly, an exploratory and applied research design was employed in this study. The research sample included 15 experienced staff working in main and related positions in Neyr Perse Company. After reviewing the literature and the Project Management Body of Knowledge (PMBOK), 32 risk factors were identified and their number reduced to 17 risks using the expert opinions via the fuzzy Delphi technique run through three stages. The results of the confirmatory factor analysis showed that all risks were confirmed by the members of the research sample. Then the identified risks were structured and ranked using fuzzy DEMATEL and fuzzy ANP techniques. The final results of the study showed that the political and economic sanctions had the highest weight followed by foreign investors' attraction and the lack of regional infrastructure. (B. Barghi).The oil and gas industry is the most important industry in terms of financial turnover and employment. Given the degree of development in the industry which depends on oil and its derivatives, new projects are initiated every day. Therefore, the number of projects in the oil and gas sector is very high. Considering the financial tunover of oil projects, the management of these projects is very important [4]. On the other hand, these projects are also at high risk which can be attributed to the high risky nature of gas and oil and the flammability and hazardous nature of their derivatives, which are often the cause of accidents in exploration and exploitation projects. For this reason, reducing the risks associated with oil projects, especially in exploration and exploitation projects, is very important [5]. Gas and oil projects are associated with a variety of risks in the present era. Therefore, the management of project risks is critical to the survival of these projects. Risk management is one of the phases of project management and project risk ranking is a key part of the risk assessment phase in the process of project risk management. Also, according to experts and practitioners of oil industry projects, the probable impact of risks affect project objectives such as cost, time, scope and quality of the project [3]. The PMBOK standard identifies risk management at various steps and provides control programs to reduce the severity of risks. These steps are stated as follows:https://doi.

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“…In other words, the relations whose impact was higher than 0.05 were determined in the total impact matrix as shown in Table 24. [35], [36]:…”

Section: Fuzzy Anp Resultsmentioning

confidence: 99%

“…In order to determine the final ranks and design the impact model Table 22 is deffuzzified as follows [35], [36] As is clear from the calculations, 17 has the greatest impact. This means that it also affects a large number of risks and has the greatest impact.…”

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confidence: 99%

Qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions

Barghi

Sikari

2020

Heliyon

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“…As a result, there is a degree of uncertainty associated with the weight point estimates provided by the eigenvector method or any other method, including least squares, weighted least squares, logarithmic least squares, and robust regression [44,45]. There are different approaches to cope with the uncertainty in the AHP method, such as the Monte Carlo simulation [46][47][48][49][50][51] and the fuzzy set theory approach [52][53][54][55][56][57].…”

Section: Ahp For the Challenge Indicatorsmentioning

confidence: 99%

Assessing and prioritizing challenges facing bioenergy supply chain in norway: A Delphi-AHP method

Barahmand¹,

Eikeland²

2022

Int. J. EQ

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Norway is leading the share of renewable energy in Europe by almost 75%. However, the share of bioenergy in Norway's energy supply is insignificant. Bioenergy, the most common type of renewable energy, generates more energy than all other forms. This fact demonstrates the value of bioenergy, which will play an increasingly important part in the future energy mix. There are different biomass resources such as agricultural crop residues, forestry, wood processing residues, algae, dedicated energy crops, and municipal and wet organic waste. Biofuel markets in Norway are relatively immature. In past decades, bioenergy consumption in Norway ranged between 4% and 6% of the total primary energy supply. Norway has experienced a gradual increase in total energy supply of biofuels and wastes, and it has almost doubled since 1990, which is 80 petajoule in 2020. However, various barriers are hindering the development of the biomass industry. The present study aims to identify and classify Norway's biomass supply chain challenges and prioritize them using the Delphi-Analytic Hierarchy Process (AHP) method. Based on a comprehensive literature review, 42 challenges were recognized and classified into seven major categories. Then, a Delphi technique is used to define and choose the main challenges in the context of Norway through an expert panel. Finally, 4 main categories, 9 sub-categories, and 37 challenge indicators related to Norway's biomass industry were selected. Moreover, the AHP method is employed to determine the weight of the challenges using a geometric mean approach. The results show that 'high investment cost', 'Greenhouse Gas (GHG) emission', 'minor differences between the energy prices achievable for the sales of heat and electricity', and 'small market size' were the most critical challenge indicators.

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“…Five different pairs of algorithms were used in the first evaluation. Their reliability was ordered according to the principle of least squire method [47]. Here the first three algorithms were selected and used in the second-grade evaluation.…”

Section: The Evolution Of Fahp Theorymentioning

confidence: 99%

A Fuzzy Analytic Hierarchy Process-Based Analysis of the Dynamic Sustainable Management Index in Leisure Agriculture

Lin

2020

Sustainability

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Agricultural leisure is one of the development trends in modern society. However, in leisure agriculture management, managers must consider the dual characteristics of agricultural production technology and the leisure service industry. Therefore, managers often face various selection pressures during management decision-making. This study examined the following five evaluation aspects: organization and operation, leisure agricultural resources, environmental maintenance management, public facility maintenance management, and operational performance. Thereafter, according to the five evaluation aspects, 21 subprojects were further divided at the second level on the basis of different attributes. Fuzzy analytic hierarchy process (FAHP) was adopted to calculate the relative weights of various indicators, and the indicators were dynamically sorted according to their importance. Moreover, the study summarized the dynamic management indicators of leisure agriculture and contributed to research on leisure farming. The results show that managers’ approach toward leisure agriculture management can be divided into three types: active, moderate, and conservative. The indicators in which the active managers attach importance when managing leisure agricultural enterprises are clearly different from those valued by moderate and conservative managers. Finding managers who are suitable for leisure agriculture management is of great significance to leisure agriculture enterprises. Appointing managers with appropriate attitudes who can continuously improve the efficiency of enterprises and create a competitive advantage can bring sustainable business value to these enterprises.

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Monte Carlo approach to fuzzy AHP risk analysis in renewable energy construction projects

Cited by 16 publications

References 46 publications

Qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions

Qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions

Assessing and prioritizing challenges facing bioenergy supply chain in norway: A Delphi-AHP method

A Fuzzy Analytic Hierarchy Process-Based Analysis of the Dynamic Sustainable Management Index in Leisure Agriculture

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