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Keywords:Multiple criteria decision making ELECTRE III Interval-valued intuitionistic fuzzy information Investment project selection a b s t r a c t A great number of real world problems can be associated with multicriteria decision making. These problems are often characterized by a high degree of uncertainty. Interval-valued intuitionistic fuzzy sets are a generalized form of an ordinal fuzzy set to deal with this natural uncertainty. In this paper, an enhanced version of the ELECTRE method, called ELECTRE III, is extended under the interval-valued intuitionistic fuzzy environment. The advantages and strengths of ELECTRE III as a decision aid technique and interval-valued intuitionistic fuzzy sets as an uncertain framework make the proposed method a suitable choice in solving practical problems. The application of the proposed method is illustrated by the solution of an investment project selection problem.
Multiple criteria decision making methods have received different extensions under the uncertain environment in recent years. The aim of the current research is to extend the application of the MULTIMOORA method (Multiobjective Optimization by Ratio Analysis plus Full Multiplicative Form) for group decision making in the uncertain environment. Taking into account the advantages of IVIFS (interval-valued intuitionistic fuzzy sets) in handling the problem of uncertainty, the development of the interval-valued intuitionistic fuzzy MULTIMOORA (IVIF-MULTIMOORA) method for group decision making is considered in the paper. Two numerical examples of real-world civil engineering problems are presented, and ranking of the alternatives based on the suggested method is described. The results are then compared to the rankings yielded by some other methods of decision making with IVIF information. The comparison has shown the conformity of the proposed IVIF-MULTIMOORA method with other approaches. The proposed algorithm is favorable because of the abilities of IVIFS to be used for imagination of uncertainty and the MULTIMOORA method to consider three different viewpoints in analyzing engineering decision alternatives.
Purpose
Based on the emerging view of supply chains as complex adaptive systems, this paper aims to build and test an analytical model for resilience assessment surrounding supply chain risks at the level of the supply chain system and its individual tiers.
Design/methodology/approach
To address the purpose of this study, a multimethod research approach is adopted as follows: first, data envelopment analysis (DEA) modelling and fuzzy set theory are used to build a fuzzy network DEA model to assess risk resilience of the overall supply chains and their individual tiers; next, the proposed model is tested using a survey of 150 middle- and top-level managers representing nine industry sectors in Iran.
Findings
The survey results show a substantial variation in resilience ratings between the overall supply chains characterizing nine industry sectors in Iran and their individual tiers (upstream, downstream and organizational processes). The findings indicate that the system-wide characteristic of resilience of the overall supply chain is not necessarily indicative of the resilience of its individual tiers.
Practical implications
High efficiency scores of a number of tiers forming a supply chain are shown to have only a limited effect on the overall efficiency score of the resulting supply chain. Overall, our research findings confirm the necessity of adopting both the system-wide and tier-specific approach by analysts and decision makers when assessing supply chain resilience. Integrated as part of risk response and mitigation process, the information obtained through such analytical approach ensures timely identification and mitigation of major sources of risk in the supply chains.
Originality/value
Supply chain resilience assessment models rarely consider resilience to risks at the level of individual supply chain tiers, focusing instead on the system-wide characteristics of supply chain resilience. The proposed analytical model allows for the assessment of supply chain resilience among individual tiers for a wide range of supply chain risks categorized as upstream, downstream, organizational, network and external.
Multi-criteria decision making is an implicational field that concerns with selecting or designing the best scenarios among a finite set of scenarios based on a finite set of criteria. Different methods and techniques for handling this issue have been proposed. Complex proportional assessment is an analytical tool for solving multi-criteria decision making problems. Originally, the COPRAS method has been developed for decision making under a deterministic environment. Since uncertainty is an unavoidable property of decision making due to a lack of knowledge, this paper suggests an extended form of the COPRAS method used for group decision making problems in an uncertain environment where such uncertainty is captured through a generalized form of fuzzy sets - the so called interval valued intuitionistic fuzzy sets. An algorithmic scheme for the COPRAS-IVIF method has been introduced thus examining its application with reference to two numerical examples. It seems that the recommended framework of COPRAS-IVIF can be satisfactorily implemented in decision making problems under ambiguous and ill-defined conditions.
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