An Extended Prospect Theory for Robot Evaluation and Selection considering Risk Preferences and Interactive Criteria

The evaluation and selection process can be regarded as a complex multiple criteria decision analysis (MCDA) problem which involves various interaction relationships among under high uncertain environment. In addition, the decision-makers are always bounded rational in risk decision-making process. However, current robot approach seldom considers decision-maker’s preference interactive Thus, purpose of this paper is to develop hybrid MCDA for solving problem. proposed framework, interval type-2 fuzzy set used express information provided by decision-makers. Next, distance measure numbers developed determine each criterion. Then, extended prospect theory based on Choquet integral evaluate prioritize considering criteria. Finally, case study auto industry selected exemplify application framework. After that, comparison sensitivity studies conducted further demonstrate robustness, effectiveness, reasonableness approach.