Service supplier selection under fuzzy and stochastic uncertain environments

Owing to the heterogeneity and inherent uncertainty of services, the selection of service suppliers is a complicated multi-attribute group decision-making (MAGDM) problem in which fuzzy criteria and stochastic criteria coexist. During the past few decades, many real-world supplier selection problems have been resolved using MAGDM methods. Nevertheless, extant research on supplier selection considers either fuzzy criteria or stochastic criteria, and hence most of these methods cannot address the complex and unstructured nature of contemporary service supplier selection problems. In this study, a novel technique for order preference by similarity to the ideal solution (TOPSIS) approach, integrating both fuzzy criteria and stochastic criteria, is developed; in this approach, the interval-valued intuitionistic fuzzy (IVIF) cross-entropy for fuzzy criteria and the Euclidean distance for stochastic criteria are used to acquire the rankings of alternatives. Moreover, a sensitivity analysis is conducted for a case study of hoisting service supplier selection, and a comparative analysis with other existing methods is performed to confirm the effectiveness and efficiency of the proposed approach.

FEATURES OF SELECTION OF SECONDARY MEDICAL PERSONNEL OF THE ORGANIZATION OF THE HEALTH AND RESORT SPHERE

The construction of the personnel selection process allows you to systematize work with candidates and make it more effective by using selection methods that meet the goals of the organization in the field of human resource management. If the selection is carried out intuitively and not structured, the company spends a large amount of financial, time and labor resources, while losing the opportunity to analyze the effectiveness: without fixed responsibility for the selection stages of organizational units, prescribed selection stages and requirements for the candidate at each stage, the organization cannot, if necessary, identify problems in time and promptly adjust the process. This article describes the procedures for the selection of secondary medical personnel in a sanatorium-resort organization. The analysis of the personnel selection process of a sanatorium-resort organization is carried out, the selection problems are highlighted, which the authors’ recommendations are aimed at, in particular, a competency model is developed, and a portrait of the candidate is formulated that corresponds to the competency model, job description and opinions of the participants in the selection process.

Supplier Selection Analysis Using Minmax Multi Choice Goal Programming Model

Production control, inventory and distribution is an important factor in trading activities. These three factors are discussed in a system called Supply Chain Management (SCM). Procurement of goods from a company or trading business related to suppliers. In some cases, there are several supplier that can be assessed by considering certain factors. In certain cases, the data from several factors that are considered are uncertainty, so the fuzzy approach can be used. The MINMAX Multi Choice Goal Programming model can be used to solve fuzzy supplier selection problems with linear membership function. It can be applied to selecting supplier of Brastagi Oranges. There are four suppliers, namely Jaya, Mako, Baros. Gina. There are three factor to consider, cost, quality and delivery. The decision maker select the best supplier for ordering 17000 kg Brastagi oranges. The results, the best supplier is Gina with an order quantity of 10000 kg and Mako with a total order of 7000 kg

A Weakly Informative Prior for Resonance Frequencies

We derive a weakly informative prior for a set of ordered resonance frequencies from Jaynes’ principle of maximum entropy. The prior facilitates model selection problems in which both the number and the values of the resonance frequencies are unknown. It encodes a weakly inductive bias, provides a reasonable density everywhere, is easily parametrizable, and is easy to sample. We hope that this prior can enable the use of robust evidence-based methods for a new class of problems, even in the presence of multiplets of arbitrary order.