The selection of the optimal supply is an open and crucial issue in supply chain management (SCM), which can be considered as a multi-criteria decision-making (MCDM) problem where the expression and processing of uncertain information could be involved. The purpose of this paper is to develop an elimination and choice translating reality (ELECTRE)-based MCDM method where the evaluation information is expressed and handled by a Dempster–Shafer theory (DST). DST is a primary methodology for uncertainty modeling. In this paper, the weight of the criteria and the performance of each alternative are expressed by linguistic terms and confidence levels, which are then converted to basic probability assignment (BPA) representations. To aggregate evaluations of different experts more rationally and efficiently, a discounting method in DST is presented based on the proposed concept of evidential reliability. In addition, as one family of MCDM models, the ELECTRE method is famous for its outranking relations to rank a set of alternatives. As an extension, synthetic weight, including subjective and objective weights, is applied to determine the concepts of concordance and discordance. The proposed DS-ELECTRE approach not only maintains the advantage of the DST that directly represents and handles uncertainty but also can play the role of the ELECTRE method in analyzing outranking relations among alternatives. An illustrative numerical example is conducted to demonstrate the effectiveness of the DS-ELECTRE method.

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An ELECTRE-Based Multiple Criteria Decision Making Method for Supplier Selection Using Dempster-Shafer Theory

Decision makers (DMs) have different cognitive levels in practical experience, information reserve, and thinking ability. Thus, decision information is often not completely reliable. As a tool that can effectively represent information reliability, Z-number has been studied by many scholars in recent years. Current research on Z-number assumes that differences in various parts of a Z-number can complement one another. However, in many cases, the preference of DMs for each part is difficult to determine, or DMs believe that the differences in various parts cannot be complementary. Therefore, to solve such decision problems, this paper attempts to extend the traditional MABAC method to the Z-information environment by introducing the directed distance and regret theory. The proposed method simultaneously considers the randomness and fuzziness of Z-number. An example about regional circular economy development program selection is provided to illustrate the feasibility of the proposed method. Results show that the proposed method can solve complex decision problems rationally and effectively, and it has broad application prospects.

Extended Z-MABAC Method Based on Regret Theory and Directed Distance for Regional Circular Economy Development Program Selection With Z-Information

An uncertain Z-number multicriteria group decision-making method with cloud models

Decisions are based on information, and the reliability of information affects the quality of decision-making. Z-number, produced by Zadeh, considers the fuzzy restriction and the reliability restriction of decision information simultaneously. Many scholars have conducted in-depth research on Z-number, and the concept has great application potential in the field of economic management. However, certain problems with the basic operations of Z-number still exist. Entropy is a measure of information uncertainty, and research on entropy and Z-number continues to be rare. This study initially defines the cross entropy of fuzzy restriction and that of the reliability of Z-numbers. On this basis, a comprehensive weighted cross entropy is constructed, which is used to compare two discrete Z-numbers from the perspective of information entropy. Furthermore, one extended Technique for Order Preference by Similarity to Ideal Solution approach is developed to solve a multi-criteria decision-making problem under discrete Z-context. An example of the ranking of job candidates for human resource management is then presented to illustrate the availability of the proposed method along with the sensitivity and comparative analyses for verifying the validity and applicability of the proposed method.

Kai-wen Shen

Papers

Multi-criteria decision-making method based on Smallest Enclosing Circle in incompletely reliable information environment