Probability multi-valued neutrosophic ELECTRE method for multi-criteria group decision-making

Probability multi-valued neutrosophic sets (PMVNSs) can better describe the incomplete and indeterminate evaluation information, and the ELECTRE method can rank the alternatives in the light of the outranking relations among criteria. To combine their advantages, this paper introduces an extended ELECTRE method to address multi-criteria group decision-making (MCGDM) problems with the information of PMVNSs. Firstly, we introduce the definitions of PMVNSs and the classical ELECTRE method, discuss the ELECTRE-based outranking relations for PMVNSs and analyze some properties of them. Furthermore, the probability multi-valued neutrosophic ELECTRE method is developed to address MCGDM problems based on the proposed distance measure and outranking relations for PMVNSs. Finally, a typical example for logistics outsourcing provider selection is devoted to demonstrate the feasibility of the proposed approach. Moreover, the same example-based comparisons with other existing methods are carried out, the results show our proposed approach outperforms the existing methods in solving the MCGDM problems with PMVNSs.

Prioritization of Elements Selection in Order-Picking Problems Through a Preference Model Influenced by Personality

In the purchase of products, a warehouse is an integral part between producers and customers, where the order picking is one of several operations involved. This chapter highlights the prioritization of the selection of the elements that make up an order based on the influence of the customer's personality on their preferences in order to choose the alternatives of the order. For this purpose, two approaches of personality theories are integrated in order to model the influence of personality as a factor that influences the parameter values of preference models based on outranking relations. The application case deals with an online supermarket using an intelligent virtual agent as the assistant that receives the order, who emulates the personality and preferences of the customer, selecting and delivering the best order. This chapter will emulate the behavior of decision makers, showing the impact of personality on preferences and will analyze its range of applications in problems related to the order picking.

Towards Identifying Multicriteria Outliers

This article tackles the problem of outlier detection in the multicriteria decision aid (MCDA) field. The authors propose an outlier detection method based on binary outranking relations and Local Outlier Factor (LOF) algorithm. The outlier is detected by applying LOF algorithm on the distribution of the outranking relations generated by a multicriteria outranking method. The proposed approach is illustrated on an artificial example and evaluated on a real life financial problem, the country risk problem.

Local Look at Human Trafficking

We use expert opinion to determine linear equations that aid in determining how well a local area in the state of Nebraska, USA, is doing in combating sex trafficking. The mathematical model used here can be expanded to larger regions such as states or countries. Our results are in agreement with those of Shared Hope International. We also use outranking relations to determine experts’ preferences.

The ELECTRE I Multi-Criteria Decision-Making Method Based on Hesitant Fuzzy Sets

Hesitant fuzzy set (HFS), which allows the membership degree of an element to a set represented by several possible values, is considered as a powerful tool to express uncertain information in the process of multi-criteria decision making (MCDM) problems. In this paper, we develop a hesitant fuzzy ELECTRE I (HF-ELECTRE I) method and apply it to solve the MCDM problem under hesitant fuzzy environments. The new method is formulated using the concepts of hesitant fuzzy concordance and hesitant fuzzy discordance which are based on the given score function and deviation function, and employed to determine the preferable alternative. Numerical examples are provided to demonstrate the application of the proposed method, and the influence of different numbers of alternatives on outranking relations is analyzed based on a derived sensitive parameter interval in which a change in the parameters has no effects on the set of the nonoutranked alternatives. The randomly generated numerical cases are also investigated in the framework of the HF-ELECTRE I method. Furthermore, the outranking relations obtained in the HF-ELECTRE I method with those derived from the aggregation operator-based approach and the ELECTRE III and ELECTRE IV methods are discussed.