By 2050, the global population is estimated to rise to over 9 billion people, and the global food need is expected to ascend 50%. Moreover, by cause of climate change, agricultural production may decrease by 10%. Since cultivable land is constant, multi-layered farms are feasible alternatives to yield extra food from the unit land. Smart systems are logical options to assist production in these factory-like farms. When the amount of food grown per season is assessed, a single indoor hectare of a vertical farm could deliver yield equal to more than 30 hectares of land consuming 70% less water with nearly zero usage of pesticides. In this study, we evaluated technology selection for three vertical farm alternatives via MCDM methods. Even though commercial vertical farms are set up in several countries, area is still fresh and acquiring precise data is difficult. Therefore, we employed fuzzy logic as much as possible to overcome related uncertainties. WEDBA (Weighted Euclidean Distance Based Approximation) and MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) methods are employed to evaluate alternatives.

In the process of fuzzy decision-making, ranking of fuzzy numbers is a necessity. The types of fuzzy numbers are triangular, trapezoidal, and L-R type. In the literature, there are many methods developed for ranking fuzzy numbers. These methods may produce different ranking results. Many of these methods necessitate graphical representations, complex and tedious calculations. The method developed in this paper has some advantages with respect to the other methods in both graphical representations and calculations. Applicability of the proposed method to multi-criteria decision-making methods, i.e. fuzzy scoring, fuzzy AHP and fuzzy TOPSIS methods, is shown in the paper.

R&D project selection decision is very important in two ways. First, in many organizations, R&D budget represents huge investment. Project selection decisions could be thought with the strategic objectives and plans of the firm. Second, R&D projects' organizational returns are multidimensional in nature and risky in terms of projected outcome. Real options approach helps to calculate this risky side of the selection process. This paper considers that multidimensional side of the R&D project selection process. Another consideration is the vagueness in the evaluation process. The fuzzy analytic hierarchy process, which takes monetary (fuzzy real option value) and nonmonetary (capability, success probability, trends, etc.) criteria into account, is used to make this selection among alternative R&D projects. A real case study is given to illustrate the application of the proposed approach.