Multi Attribute Group Decision Making Based On Comprehensive Cloud Under Linguistic Hesitant Fuzzy Environment And Its Application In ERP Selection

Under the background of economic globalization,the market competition is becoming increasingly intense on the market,which poses great challenges to the operation and management of the enterprises.Therefore,to enhance the competitiveness of the enterprises,modern enterprises prefer to use the Enterprise Resource Planning(ERP)system.The effective use of ERP system can improve the management level in production,operation,sales and so on.Furthermore,it brings double improvements to the operation efficiency and management control ability of enterprises.ERP system selection problem needs to construct evaluation index system,thus ERP system selection problem belongs to a class of multiple attribute decision making problems.In real decision making,decision makers can not only just use quantitative variables or qualitative variables to give evaluation information effectively because of the complexity of objective things and the inherent fuzziness of human thinking.In order to solve this question,using language hesitation fuzzy sets in decision process can not only express the preference of decision makers,but also respond to the degree of hesitation of the decision makers' evaluation information.Therefore,the application of linguistic hesitation fuzzy multiple attribute decision making in ERP systems selection problem is important.Linguistic hesitant fuzzy sets are a very useful tool to represent decision makers' preferences and describe decision makers' evaluation the uncertainty and hesitation in decision making process.In this paper,two methods based on comprehensive cloud are developed for solving multi-attribute group decision making problems with linguistic hesitant fuzzy set.Firstly,the comprehensive cloud of a linguistic hesitant fuzzy set is defined and a distance measure between two comprehensive clouds is proposed.Then,by extending the power geometric operator and the power ordered weighted geometric operator to comprehensive cloud environment,some comprehensive cloud aggregation operators are introduced,including a comprehensive cloud power geometric averaging operator,a comprehensive cloud power weighted geometric averaging operator,and a comprehensive cloud power ordered weighted geometric averaging operator.Subsequently,an uncertainty degree of a LHFS is defined,then,a method is developed to derive the weights of DMs based on the uncertainty degree.In this paper,considering the uncertainty degree of decision information and the weighted deviation among attributes,a new method is proposed to derive the attribute weights.Thus,two linguistic hesitant fuzzy multi-attribute decision making methods based on comprehensive cloud are proposed in this paper.The two methods are linguistic hesitant fuzzy multi-attribute decision making methods based on comprehensive cloud power weighted geometric operator and linguistic hesitant fuzzy multi-attribute decision making methods based on comprehensive cloud power order weighted geometric operator,respectively.Finally,the applicability and effectiveness of the proposed method are illustrated by a case study and a comparative analysis.