Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method

Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making

Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) Fuzzy Analytical Hierarchy Process for the evaluation of the decision maker weights coupled with (2) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis

Constrained k\mathbf {k}-means algorithm for resource allocation in mobile cloudlets

summary:With the rapid increase in the number of mobile devices connected to the Internet in recent years, the network load is increasing. As a result, there are significant delays in the delivery of cloud resources to mobile users. Edge computing technologies (edge, cloudlet, fog computing, etc.) have been widely used in recent years to eliminate network delays. This problem can be solved by allocating cloud resources to the cloudlets that are close to users. The article proposes a clustering-based model for the optimal allocation of cloud resources among cloudlets. The proposed model takes into account user activity, usage frequency of cloud resources, the physical distance between users and cloud resources, as well as the storage capacity of cloudlets for optimal allocation of cloud resources in cloudlets. The proposed model was formalized as a constrained $k$-means method and an algorithm was developed to solve it. The MATLAB 2022a toolkit was used to evaluate the efficiency of the proposed algorithm. The obtained results revealed that the algorithm is promising

The content of innovations and structural analysis of their features in the formation of information economy

Abstract: The paper presents the relevance of economic development of the information society on the basis of ICT and innovation. Socio-economic essence of innovation, as well as various scientific and theoretical approaches to innovation and formation of innovation theory are analyzed. The types, objectives, content and definitions of innovation are studied. Generalized classification features of innovations are explained, some additions are made in accordance with the new economic conditions. Some factors influencing, accelerating and slowing down the development of innovations and presented. In accordance with the requirements of the information society, content and composition of new electronic innovation based on the achievements of the ICT sector are analyzed. The concept of e-innovation is proposed for the mass dissemination and application of innovation in other areas

Query-based multi-documents summarization using linguistic knowledge and content word expansion

In this paper, a query-based summarization method, which uses a combination of semantic relations between words and their syntactic composition, to extract meaningful sentences from document sets is introduced. The problem with current statistical methods is that they fail to capture the meaning when comparing a sentence and a user query; hence there is often a conflict between the extracted sentences and users’ requirements. However, this particular method can improve the quality of document summaries because it is able to avoid extracting a sentence whose similarity with the query is high but whose meaning is different. The method is executed by computing the semantic and syntactic similarity of the sentence-to-sentence and sentence-to-query. To reduce redundancy in summary, this method uses the greedy algorithm to impose diversity penalty on the sentences. In addition, the proposed method expands the words in both the query and the sentences to tackle the problem of information limit. It bridges the lexical gaps for semantically similar contexts that are expressed using different wording. The experimental results display that the proposed method is able to improve performance compared with the participating systems in DUC 2006. The experimental results also showed that the proposed method demonstrates better performance as compared to other existing techniques on DUC 2005 and DUC 2006 datasets

Sentence similarity measure in Deletion strategy.

<p>Sentence similarity measure in Deletion strategy.</p

Sentence similarity computation model.

<p>Sentence similarity computation model.</p

Use of Location Method amongst 560 sentences.

<p>Use of Location Method amongst 560 sentences.</p

Number of source sentences combined in each summary sentence.

<p>Number of source sentences combined in each summary sentence.</p