Expertons and uncertain averaging operators versus correlational approaches: A case study on corporate social responsibility and effectiveness

The purpose of this paper is to explore the relationship between corporate social responsibility (CSR), work-life balance (WLB) and effectiveness by comparing a correlational approach, expertons method and uncertain averaging operators (uncertain average [UA], uncertain weighted average [UWA], uncertain probabilistic aggregation [UPA] and uncertain probabilistic weighted averaging [UPWA])

An Exploration of Wisdom of Crowds using Neutrosophic Cognitive Maps

t. The wisdom of crowds (WOC) is a theory where it is believed that a multitude of people, unknown to each other and not experts in some subject, can reach more accurate conclusions on this subject than each of them would achieve individually; it could even have more accuracy than the result that a group of experts would obtain. This theory can be used to obtain information from the individual knowledge of an inexperienced crowd, including knowledge on complex phenomena. In this paper, the complex phenomenon is represented with the help of Neutrosophic Cognitive Maps (NCM), which allow us to capture the cause-effect relations among the concepts according to each of the individuals’ judgments. In this case, a dynamic processing of the results is carried out. The NCMs are aggregated following the WOC principles using an aggregation algorithm, which is based on the Fuzzy Negative-Positive-Neutral (NPN) logic. The advantage of using NCM is that indeterminacy is included in the modeling, thus individuals can express their opinions more reliably

Binary Particle Swarm Optimization based Biclustering of Web usage Data

Web mining is the nontrivial process to discover valid, novel, potentially useful knowledge from web data using the data mining techniques or methods. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. With the rapid development of biclustering, more researchers have applied the biclustering technique to different fields in recent years. When biclustering approach is applied to the web usage data it automatically captures the hidden browsing patterns from it in the form of biclusters. In this work, swarm intelligent technique is combined with biclustering approach to propose an algorithm called Binary Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The main objective of this algorithm is to retrieve the global optimal bicluster from the web usage data. These biclusters contain relationships between web users and web pages which are useful for the E-Commerce applications like web advertising and marketing. Experiments are conducted on real dataset to prove the efficiency of the proposed algorithms

Quantify resilience enhancement of UTS through exploiting connect community and internet of everything emerging technologies

This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everything (IoE) and the new trend of the Connected Community (CC). A conceptual extension of Functional Resonance Analysis Method (FRAM) and its formalization have been proposed and used to model UTS complexity. The scope is to identify the system functions and their interdependencies with a particular focus on those that have a relation and impact on people and communities. Network analysis techniques have been applied to the FRAM model to identify and estimate the most critical community-related functions. The notion of Variability Rate (VR) has been defined as the amount of output variability generated by an upstream function that can be tolerated/absorbed by a downstream function, without significantly increasing of its subsequent output variability. A fuzzy based quantification of the VR on expert judgment has been developed when quantitative data are not available. Our approach has been applied to a critical scenario (water bomb/flash flooding) considering two cases: when UTS has CC and IoE implemented or not. The results show a remarkable VR enhancement if CC and IoE are deploye

Group-decision making with induced ordered weighted logarithmic aggregation operators

This paper presents the induced generalized ordered weighted logarithmic aggregation (IGOWLA) operator, this operator is an extension of the generalized ordered weighted logarithmic aggregation (GOWLA) operator. It uses order-induced variables that modify the reordering process of the arguments included in the aggregation. The principal advantage of the introduced induced mechanism is the consideration of highly complex attitude from the decision makers. We study some families of the IGOWLA operator as measures for the characterization of the weighting vector (...

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified