Abstract
The evaluation and selection process can be regarded as a complex multiple criteria decision analysis (MCDA) problem which involves various interaction relationships among criteria under high uncertain environment. In addition, the decision-makers are always bounded rational in the risk decision-making process. However, the current robot evaluation and selection approach seldom considers the decision-maker’s risk preference and interactive criteria under high uncertain environment. Thus, the purpose of this paper is to develop a hybrid MCDA approach for solving the robot evaluation and selection problem. In the proposed framework, the interval type-2 fuzzy set is used to express the uncertain evaluation information provided by decision-makers. Next, the distance measure of interval type-2 fuzzy numbers is developed to determine the fuzzy measure of each criterion. Then, the extended prospect theory based on developed Choquet integral is proposed to evaluate and prioritize the robot by considering the decision-maker’s risk preference and interactive criteria. Finally, a case study of robot evaluation and selection in the auto industry is selected to exemplify the application of the proposed framework. After that, comparison and sensitivity studies are conducted to further demonstrate the robustness, effectiveness, and reasonableness of the developed approach.
Highlights
In recent years, Industry 4.0 has been used to describe the features of the digitized and automated manufacturing industry [1]
Some important techniques are used to depict the uncertain evaluation information from various experts. ese techniques include triangular fuzzy numbers (TFNs) [5, 6], generalized interval-valued fuzzy numbers (GIFNs) [7], interval 2-tuple linguistic terms set (ITLTS) [8], hesitant 2-tuple linguistic term sets (HTLTS) [9], interval type-2 fuzzy set (IT2FS) [10], interval-valued Pythagorean uncertain linguistic set (IVPFLS) [11], interval-valued intuitionistic hesitant fuzzy set (IVIHFS) [3], and hesitant fuzzy linguistic term sets (HFL) [2]. Among these uncertainty expression methods, the interval type-2 fuzzy set can effectively deal with the intra- and interuncertainty of the evaluation process [12]; the interval type-2 fuzzy set is selected to depict the uncertain evaluation information in this paper
No research develops prospect theory-based prioritization method by using Choquet integral and interval type-2 fuzzy set for robot evaluation and selection. erefore, we proposed an extended prospect theory-based prioritization approach to address robot evaluation and selection problem with interactive criteria under interval type-2 fuzzy environment
Summary
Industry 4.0 has been used to describe the features of the digitized and automated manufacturing industry [1]. Ese techniques include triangular fuzzy numbers (TFNs) [5, 6], generalized interval-valued fuzzy numbers (GIFNs) [7], interval 2-tuple linguistic terms set (ITLTS) [8], hesitant 2-tuple linguistic term sets (HTLTS) [9], interval type-2 fuzzy set (IT2FS) [10], interval-valued Pythagorean uncertain linguistic set (IVPFLS) [11], interval-valued intuitionistic hesitant fuzzy set (IVIHFS) [3], and hesitant fuzzy linguistic term sets (HFL) [2] Among these uncertainty expression methods, the interval type-2 fuzzy set can effectively deal with the intra- and interuncertainty of the evaluation process [12]; the interval type-2 fuzzy set is selected to depict the uncertain evaluation information in this paper
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
