Identify and Prioritize Risks of Construction Projects Based on Fuzzy Logic (Case Study: Construction Project of Iranian Investment and Sustainable Development Company)

The purpose of the research was to identify and rank risks in construction projects of Iranians investment and Sustainable Development Company. This descriptive study based on purpose and on the basis of data collection is the survey. The study society consisted of 25 experts in construction projects. The data collected through a questionnaire which is then used to calculate the reliability and validity researcher. Thus, using literature review and interviews with experts, more than 100 risks were identified and were divided based on risk factors and risk breakdown structure, for weighting criteria, network analysis process which is used to obtain the internal relationship between the criteria of DIMATEL fuzzy method is used, then rankings risks were done using fuzzy TOPSIS algorithm. The results showed that, given the vague nature of the data in most projects, the proposed model is suitable for the real world.


Introduction
Risk management is one of 10 areas of project management knowledge that is particularly important in terms of theory and practice and despite the publication of numerous articles on the subject, little and substantial deficiencies are in this area in the real world.
Effective risk management project guides manager to achieve the desired benefits such as identifying options activity, increasing the likelihood of achieving the project objectives, to improve the chances of success, reduce unexpected events, achieving accurate estimates (by reducing uncertainty), and the effects of reducing the frequency.(Bannerman, 2008) On the other hand, project management, application of knowledge, skills, tools and techniques related to project activities to meet project requirements.(PMI, 2013) Of the year 1990, several models have been presented for risk management projects with the aim of increasing their success, such as SHAMPU model (Chapman & Ward, 1997), ALARM (2002), the PRMA (2004), the PRAM (1997), Smith model (2002), Leach model (2000), etc.The most famous and most widely recognized standard among standards is Body of Knowledge of the Project Management (PMBOK).This standard describes all the necessary processes for project management process in the form of 47.
According to the definition of knowledge management guide (2013) risk is said to events have occurred in the future that is uncertain and in case of a positive or negative effect on the project.Risks with positive impact called desired or opportunities risk, and the risks with negative impact is called or threat or undesirable risk.According to Mark research et al. (2004) risk is the potential against complexities and difficulties with regard to complete project activities and achieve the project objectives.
Risk is inherent in all projects.Risk cannot be completely removed or destroyed, but with effective management can affect the project.Project risk is an integral part of any project, it must be managed.In fact, systematic project risk management process involves planning for the identification, analysis, response and risk monitoring project.This includes management processes, tools and techniques that help project managers to maximize likelihood of positive events and minimizing the likelihood of adverse events.(Azar, 2010) PMBOK standard summarized risk management process as below: 1. Identifying risks 2. Analysis of risks 3. Responding to risks

Risk Control
With a general, the risk management process is divided into two main stages of risk assessment (including identification and risk analysis) and respond to them.(Miller, 2005) According to Kunero (2003), all equally important step risk management process and may be incomplete each of the steps leading to ineffective risk management.
Because the success of the project, the different metrics to measure stakeholders to assess the success of the project is difficult.(Yon Chang et al., 2009) For construction companies face the risk of uncertainty, by evaluating their impact on the objectives of the project are important.Because of this it can be concluded that with a bit of a risk which is more risky projects and we can plan for potential sources of risk in any project and any source (origin) to manage the construction period.(Zayed et al., 2008) In the meantime, use of fuzzy theory because of the uncertainty in risk management concept, widely used in the research area in construction management.Using fuzzy set theory, data can be defined vaguely and phrases such as low probability, high impact or high risk.
These statements may be significantly showed a number, but the fuzzy set theory provides a tool that can define this expression with mathematical logic.(Jafari, 2001) The theory is applied in confusion and uncertainty.This theory has not been capable to express many of the concepts and mathematically precise and provide reasoning, inference, control and decision-making under uncertainty.(Aydin, 2004) According to the studies that have been done in the field of risk assessment and ratings, can be found to various aspects of the issue.Perry and Hayes (1985) gave a list of factors, risks and resources it into 3 parts: contractors, consultants and employers.Cooper and Chapman (1987) Classified the risks according to their importance and the nature and risks divided have into two groups: primary and secondary.(Abdou, 1996) Risk is classified into 3 groups: financial, time and design.Zhang et al. (2007) classified risk factors as: human, sites, material and equipment.In general, project risks, there are several ways to classify and select a logical method depends on the specific objectives of the research.(Zou et al., 2007) Also, several research have been conducted to rank risk projects, including Bakarini and Archer (2001) describes a method of using the grading process for ranking project risk project risk associated with contract services department, Western Australia is the government agency's management.Due to the fact that at each stage of the project risk management process different tools can be used.Ebrahimnejad et al. (2010) used Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) and Fuzzy Linear Programming Technique for Multidimensional analysis of Preference (FLINMAP) in projects to build, operate and transfer.They are in their proposed model, the risk of project construction, implementation and transfer of Iran's power plants identify and evaluate and rank the most important risks.
In research was conducted by Olfat and Jalali, (2010) project risks interchange construction projects in the province were identified based on the standard of knowledge of project management, then fuzzy hierarchical analysis and fuzzy TOPSIS methods were used for prioritization.Also similar studies by other Mojtahedi et al. (2010), Mousavi et al. (2011), Azari Karimi et al. (2011), Sayyadi et al. (2011) conducted that several criteria were determined based on likelihood and impact of risks on project objectives with different weights.
Therefore, taking into account the research literature, this paper aims to identify, assess and respond to risks in a timely manner in order to reduce adverse impacts and increase the desired effects.This study was conducted at the investment company of Iranian civil and sustainable development.In short, looking for an analytical model fits into the project risk management is evaluated.
In this regard, researchers sought to answer the following questions: Step Three: In this step, using the seven expert organization, to weighting of the criteria and ranking risks were discussed.This process is given below: First step: In this step, weighting criteria will be discussed.Because, according to experts, there is interdependence between the criteria and network analysis process will be used for that interrelation between them, DIMATEL fuzzy method is used.This process is given below: First step -first stage: In this phase, we assume that there is no dependence between criteria.From experts want to use the words of a language table 2 between their judgment.Output of the questionnaire fuzzy numbers in Table 3 below.
Then, using a method developed by Bezbora and Beskes (2007), weight of criteria is given in Table 4.Because the process is very time consuming calculations by this method, it was coded using MATLAB software.The impact of the measures on each other using the experience of experts was drawing schematically shown in First step -third stage: In this step interdependence matrix obtained from the first phase of the second phase of the weight factors is applied.
Thus weighting of criteria taking into account the interdependence between them is obtained.The result of this calculation is given below:  A chance encounter with infrastructure projects such as water, electricity, etc. and various problems in addressing these rebels 0.437283 Change managers and officials associated with the project 0.295018 Non-approval of the plans, the proposed amendments in the project execution Step Seven: In this step, based on the coefficient value, proximity to risks is ranked.The risk that the proximity coefficient is the highest priority is higher.
In the following risks listed in order of importance: According to the ranking of risks, it provides managers and decision makers prioritize them according to priority to manage organizational risks.This ranking is important in the sense that if an organization to meet, confront and promotion of these risks are the limited resources available, should act on the basis of risks to prevent the deviation from the objectives of the project.According to Pareto's 80-20 rule, it is recommended to focus on the 20 percent of major risks, should be avoided up to 80 percent of the deviation from the objectives of the project.

Analysis of Research Results
In this study, a model was presented for risk management projects in conditions of uncertainty regarding the conditions in the country and the status of construction projects.The most important aspect of research innovation models that are consistent with real world conditions.However, in the analysis and solution models were presented as well as new approaches.
In this study, an appropriate structure are presented for classification of risks in construction projects and risk analysis helps to identify risks.With the addition of library studies, the most common risks in construction projects of the country were identified that a few changes can be used to the country's other building projects.In the next step was to develop new models for risk assessment taking into account the preferences of decision-makers the ability to systematically.The proposed model for the evaluation and selection of timely and appropriate responses to risks also considers the different targets and selects the appropriate measures to be effective....In short, research and analysis in the areas of innovation is that the model has to mention some of them:  Development of a hierarchical structure in order to consider the different criteria in risk assessment tailored to the preferences of decision-makers  Given the interdependence between the various criteria of risk assessment  Compatibility index calculated paired comparisons in terms of fuzzy  Taking into account the standards of the time, cost, quality, range and performance risk assessment  Innovative methods for risk assessment  Using fuzzy logic in risk assessment and response to further correspondence with the real world In terms of applications using different methods, the most common risks in construction projects were identified.Also, suitable structural failure risks in construction projects were presented and finally a model for ranking risks according to different preferences of decision-makers was developed.Therefore, we see a practical sense, this research suitable for deployment provides risk management in construction projects.

Table 1 .
What are the major risks in construction projects?Output of program R

Table 2 .
Linguistic scale to determine the significance of paired comparisons

Table 3 .
Table pairwise comparisons completed by the group of experts

Table 4 .
Weight criteria regardless of interdependence

First step -second stage:
In this stage the following 5 steps, calculating the matrix interdependence through DIMATEL phase.