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

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.

Background: Headaches have not only medical but also great socioeconomic significance, therefore, it is necessary to evaluate the overall impact of headaches on a patient’s life, including their work and work efficiency. The aim of this study was to determine the impact of individual headache types on work and work efficiency. Methods: This research was designed as a cross-sectional study performed by administering a questionnaire among employees. The questionnaire consisted of general questions, questions about headache features, and questions about the impact of headaches on work. Results: Monthly absence from work was mostly represented by migraine sufferers (7.1%), significantly more than with sufferers with tension-type headaches (2.23%; p = 0.019) and other headache types (2.15%; p = 0.025). Migraine sufferers (30.2%) worked in spite of a headache for more than 25 h, which was more frequent than with sufferers from tension-type and other-type headaches (13.4%). On average, headache sufferers reported work efficiency ranging from 66% to 90%. With regard to individual headache types, this range was significantly more frequent in subjects with tension-type headaches, whereas 91–100% efficiency was significantly more frequent in subjects with other headache types. Lower efficiency, i.e., 0–40% and 41–65%, was significantly more frequent with migraine sufferers. Conclusions: Headaches, especially migraines, significantly affect the work and work efficiency of headache sufferers by reducing their productivity. Loss is greater due to reduced efficiency than due to absenteeism.

Logistics distribution is adaptive, dynamic and open self-organizing system, which is maintained by flows of information, materials, goods, funds and energy. This article presents biological intelligence for modelling and optimization on vehicle routing problem (VRP) of logistics distribution. The aim of this research is to create a novel hybrid model including genetic and firefly algorithms in routing heterogeneous fleet of vehicles in logistics distribution system. The proposed hybrid model in routing heterogeneous fleet VRP is tested on realistic data set in Serbian company ‘Carnex Ltd’. The experimental results of this method are compared with the empirical results and show that the experimental results obtained by new hybrid genetic–firefly model are better then empirical results in the company.