A new fuzzy multi-objective model for selecting capital projects in the public sector

In evaluating projects, there are many qualitative criteria, weighting, and quantifying, which have no definitive nature and are associated with various ambiguities. Also, because of the relationship between these conflicting criteria (goals), no single and multip optimal solutions (non-dominant set) should be sought. Because of the relationship between these inconsistent criteria (goals), no single and multiple optimal solutions (non-dominant set) should be sought. Accordingly, this study aims to provide an appropriate approach to develop a model for selecting construction projects in the public sector based on a mathematical multi-objective fuzzy model, which can cover the multi-objective nature of the problem and consider inherent inaccuracies and problem uncertainties. This paper first converts the model to a non-linear model by fractional planning concepts, defuzzification according to Jimenez and Yang approaches, then solves by a non-dominated sorting genetic algorithm (NSGA-II) to provide a more comprehensive model for governmental project selection public when allocating budget. This paper is attempted to develop a new model for selecting construction projects while considering the uncertainty of parameters using fuzzy theory in the public sector to show the performance of the developed model. The fuzzy model solution is compared with the deterministic model to analyze the results. The results show the improvements reflect the success rate of accomplishment for the corresponding goals in the fuzzy model compared to the exact one.