Combination of customer needs and quantitative data is an idea to produce a various value. Therefore, this research proposed method for multidisciplinary design optimization of hub airport which optimized customer needs and quantitative data simultaneously. For customer needs, target of tourism and season were assigned into design variables and optimal weight was calculated by using SGD method. Design variables of quantitative data were number of transit, transportation fee and time from airport to World Heritage, and calculated value by using AHP which Monte Carlo simulation was applied for updating optimal value. To obtain optimal value for customer needs, review of tourism was extracted by text mining and count number of review in each World Heritage, word rating point was decided to calculate the weight of each World Heritage. Next, results of customer needs and quantitative data were normalized for collaborative optimization. Finally, the results showed a various optimal solution obtained for each design variable.