International Journal of Industrial Engineering & Production Research

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Implementation of the risk management concepts into construction practice may enhance the performance of project by taking appropriate response actions against identified risks. This research proposes a multi-criteria group decision making approach for the evaluation of different alternative response scenarios. To take into account the uncertainties inherent in evaluation process, fuzzy logic is integrated into the revaluation process. To evaluate alternative response scenarios, first the collective group weight of each criterion is calculated considering opinions of a group consisted of five experts. As each expert has its own ideas, attitudes, knowledge and personalities, different experts will give their preferences in different ways. Fuzzy preference relations are used to unify the opinions of different experts. After computation of collective weights, the best alternative response scenario is selected by the use of proposed fuzzy group decision making methodology which aggregates opinions of different experts. To evaluate the performance of the proposed methodology, it is implemented in a real project and the best alternative responses scenario is selected for one of the identified risks.

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Allocation of construction risks between clients and their contractors has a significant impact on the total construction costs. This paper presents a system dynamics (SD)-based approach for quantitative risk allocation. Using the proposed SD based approach, all the factors affecting the risk allocation process are modeled. The contractor’s defensive strategies against the one-sided risk allocation are simulated using governing feedback loops. The full-impact of different risk allocation strategies may efficiently be modeled, simulated and quantified in terms of time and cost by the proposed object-oriented simulation methodology. The project cost is simulated at different percentages of risk allocation and the optimum percentage of risk allocation is determined as a point in which the project cost is minimized. To evaluate the performance of the proposed method, it has been implemented in a pipe-line project. The optimal risk allocation strategy is determined for the inflation risk as one of the most important identified risks.

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An equitable risk allocation between contracting parties plays a vital role in enhancing the performance of the project. This research presents a new quantitative risk allocation approach by integrating fuzzy logic and bargaining game theory. Owing to the imprecise and uncertain nature of players’ payoffs at different risk allocation strategies, fuzzy logic is implemented to determine the value of players’ payoffs based on the experience and subjective judgment of experts involved in the project. Having determined the players' payoffs, bargaining game theory is then applied to find the equitable risk allocation between the client and contractor. Four different methods including symmetric Nash, non-symmetric Nash, non-symmetric Kalai–Smorodinsky and non-symmetric area monotonic are implemented to determine the equitable risk allocation. To evaluate the performance of the proposed model, it is implemented in a pipeline project and the quantitative risk allocation is performed for the inflation risk as one of the most significant identified risks.