Svetlana Simić

Insolvency prediction for assessing corporate financial health

The prediction of corporate financial failure, crucial for the prevention and mitigation of economic downturns in a national economy, requires the categorization of healthy and unhealthy companies. This study examines the case of Serbia and applies multivariant statistical methods and specific artificial neural network architectures—the self-organizing map (SOM)—to assess the corporate financial health of various companies. Financial ratios drawn from corporate balance sheets become the independent variables in a multivariate discriminant analysis (MDA). These financial ratios and the discriminant Z-score in the MDA form the input for the SOM, which creates a hybrid MDA-SOM model that is capable of predicting corporate financial insolvency. The experimental results of this research correctly estimate company financial health in 95% of cases. These are reliable predictions that are comparable with similar studies in other countries.

50 years of fuzzy set theory and models for supplier assessment and selection: A literature review

Abstract Supplier assessment and selection mapping as an essential component of supply chain management are usually multi-criteria decision-making problems. Decision making is the thought process of selecting a logical choice from the available options. This is generally made under fuzzy environment. Fuzzy decision-making is a decision process using the sets whose boundaries are not sharply defined. The aim of this paper is to show how fuzzy set theory, fuzzy decision-making and hybrid solutions based on fuzzy can be used in the various models for supplier assessment and selection in a 50 year period.

An approach to efficient business intelligent system for financial prediction

A concept of business intelligent system for financial prediction is considered in this paper. It provides data needed for fast, precise and good business decision support to all levels of management. The aim of the project is the development of a new online analytical processing oriented on case-based reasoning (CBR) where a previous experience for every new problem is taken into account. Methodological aspects have been tested in practice as a part of the management information system development project of “Novi Sad Fair”. A case study of an improved application of CBR in prediction of future payments is discussed in the paper.

Computer-Assisted Diagnosis of Primary Headaches

Headache is not a disease which typically shortens ones life. However, it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European Community. While the diagnostic criteria developed by the International Headache Society (IHS) have been extensively used in the epidemiological research, there is no such a tool which helps physicians make diagnoses. This research focussed on diagnosing certain primary headache types in working people employing the rule-based fuzzy logic system. The rules were facilitated by the application of the IHS criteria for headache types. Clinical experience was used to extend the established rules and improve the system. The proposed system is in the starting phase of the implementation at the Clinical Centre Vojvodina, Institute of Neurology in Novi Sad.

A Review: Approach of Fuzzy Models Applications in Logistics

Logistics is the process of managing the flow and storage of material and information across the entire organisation with the aim to provide the best customer service in the shortest available time at the lowest cost. Long haul delivery, warehousing, fleet maintenance, distribution, inventory and order management are all examples of logistics problems. This paper outlines some current approaches of fuzzy models which are implemented in the terms of potential benefits gained in logistics domain in order to mitigate the uncertainty and risks of the current business turbulent environment and global world financial crises.

Hybrid artificial intelligence approaches on vehicle routing problem in logistics distribution

Biological intelligence for modelling and optimization on vehicle routing problem of logistics distribution and supply chain management systems are presented in this paper. Logistics distribution is adaptive, dynamic, and open self-organizing system, which is maintained by flows of information, materials, goods, funds, and energy. The aim of this research is to summarize different individual bio-inspired methods, evolutionary computing, genetic algorithm, ant colony optimization, artificial immune systems, and to obtain power extension of these hybrid approaches. In general, these bio-inspired hybrid approaches are more competitive than the classical problem-solving methodology including improvement heuristics methods or individual bio-inspired methods and their solutions in logistics distribution and supply chain management applications.

A Hybrid Analytic Hierarchy Process for Clustering and Ranking Best Location for Logistics Distribution Center

Facility location decisions play a critical role in the strategic design of supply chain networks. This paper discusses facility location problem with focus on logistics distribution center (LDC) in Balkan Peninsula. Methodological hybrid Analytical Hierarchy Process (AHP) and k-means method is proposed here and it is shown how such a model can be of assistance in analyzing a multi criteria decision-making problem. This research represents a continuation of two existing studies: (1) PROMETHEE II ranking method; and (2) combine Greedy heuristic algorithm and AHP. The experimental results in our research could be well compared with other official results of the feasibility study of the LDC located in Balkan Peninsula.

Evolutionary approach in inventory routing problem

Most companies recognize the need for the integration and coordination of various components in logistics and supply chain management as an important factor. This paper presents an evolutionary approach to modeling and optimization on inventory routing problem of inventory management, logistics distribution and supply chain management. The aim of this research is to present different individual evolutionary approach, and to obtain power extension of these hybrid approaches. In general, these evolutionary hybrid approaches are more competitive than classic problem-solving methodology including improved heuristics methods or individual bio-inspired methods and their solutions in inventory management, logistics distribution and supply chain.

Automatic diagnosis of primary headaches by machine learning methods

Primary headaches are common disease of the modern society and it has high negative impact on the productivity and the life quality of the affected person. Unfortunately, the precise diagnosis of the headache type is hard and usually imprecise, thus methods of headache diagnosis are still the focus of intense research. The paper introduces the problem of the primary headache diagnosis and presents its current taxonomy. The considered problem is simplified into the three class classification task which is solved using advanced machine learning techniques. Experiments, carried out on the large dataset collected by authors, confirmed that computer decision support systems can achieve high recognition accuracy and therefore be a useful tool in an everyday physician practice. This is the starting point for the future research on automation of the primary headache diagnosis.

Rule-Based Fuzzy Logic System for Diagnosing Migraine

This research focussed on diagnosing migraine types in working people employing the rule-based fuzzy logic system. Migraine is not a disease which typically shortens ones life. However, it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European Community. The diagnostic criteria developed by the International Headache Society (IHS) have been used in epidemiological researches, but there is no such tool which helps physicians make diagnoses. The rules were facilitated by the application of the IHS criteria for migraine types. Clinical experience was used to extend the established rules and improve the system. The proposed system is in the starting phase of the implementation at the Clinical Centre Vojvodina, Institute of Neurology in Novi Sad.