Location selection is a multi dimensional issue which requires consideration of quantitative and qualitative evaluation criteria. Some of these criteria may have imprecise and uncertain data which make the location selection decision hard to progress. Although many multi attribute decision making (MADM) techniques are utilized in location decision study field, there is a lack of studies which provide solutions by considering high number of supply chain uncertainties. In this study, against the drawbacks of traditional MADM techniques, a novel MADM approach is applied for location decision under high uncertainty as a first time. In the proposed model, a new notion named as cloud based design optimization (CBDO) is utilized because CBDO can take into consideration certain and uncertain factors simultaneously. Furthermore, it provides robust solution within worst case scenario to existing approaches by mediating between aspects of fuzzy set theory and probability distributions. Robustness enables decision makers have managerial and operational foresights about possible unexpected situations, and take necessary actions against risk. An illustrative example is conducted in warehouse location selection problem area to indicate the performance of the proposed approach. It is revealed out that location decision is very sensitive to the consideration of uncertainty and CBDO can be a helpful supportive tool for decision makers in providing solution under high uncertainty. 
A novel multi attribute decision making approach for location decision under high uncertainty