**3. Conclusion**

In this research, a linear mixed-integer model was proposed to solve a project selection problem and provide RRSs. According to objective functions, this model firstly aims to select projects with the highest net profit and risk response effects. Secondly, these projects should be carried out with minimum resource and implanting risk responses costs. The model is solved to select the most desirable projects and risk response strategies to deal with risk events. The main contribution of this research is combining of project selection from a portfolio and calculation of risk response effect. In addition, because of environmental effects, some parameters (including the cost of human, machine, material, risk response effect, etc.) were considered as fuzzy numbers. Fuzzy Me measure is considered to deal with the uncertain parameters of the proposed model. To solve the model ten building project were studied, and Net profit and resources costs were considered as objective functions. Finally, optimal allocation of risk response strategies was determined. TH method was used to solve the model, which was coded in GAMS. Results showed that increasing budgets in sample problem, led to higher net profit and less projects costs. The sensitivity analysis of the case study showed the necessity of the trade-offs between maximizing profit and minimizing projects cost. At last, Pareto frontier was analyzed. Results indicate that this model can act as a powerful criterion and help project managers to increase desirable impacts of a solution before implementing the project. Also, uncertain parameters like robust programming can be determined to cover the limitations of the designed model. Moreover, since the presented model is categorized as an NP-hard problem, meta-heuristic algorithms may be utilized to solve the model.

*Fuzzy Approach Model to Portfolio Risk Response Strategies DOI: http://dx.doi.org/10.5772/intechopen.95009*
