Computational methods are, among other things, widely used in operational research. Operational research is a complex interdisciplinary field that deals with the problems of decision-making in real conditions, considering all the factors that affect the problem directly or indirectly, in order to find the best, i.e. optimal solution. As there is a growing need for continuous process improvement, there is a growing presence of operational research methods for various real-life problems. The transportation problem is one of the segments of research within operational research. It aims to determine the optimal program of distribution of a certain type of commodity from sources (points of origin) to destinations. The sources are the places where the commodity leaves (the warehouse), while the destinations are the ending points to which the commodity should be transported (in our case -the store). As a criterion for optimizing the transportation of goods, the request for minimizing the total transportation costs is most often taken. In the case of transportation problem, the objective function expresses the total transportation costs, while the limiting conditions are determined by the supply of individual sources (warehouses), i.e. the demand of individual destinations (stores). This paper discusses the possibility of applying operational research methods in the service sector. The aim of the research part of the paper is to find the optimal solution for real data of a given problem, simulating different conditions and constraints. An experimental analysis was performed for the problem of warehouse operations, and the goal was to minimize the costs of transporting goods. Two different methods were applied in order to determine the optimal solution. Based on the obtained results and their analysis, conclusions were made as to whether the problem was solved.

New measures are being taken in the EU member states for flexible and scalable solutions in monitoring wastewater quality. The latest scientific studies have further confirmed the presence of SARS-CoV2 virus in wastewater. This virus was also detected in stool samples of patients with COVID-19 symptoms, but also in asymptomatic cases of the disease, which confirms the possibility of faecal-oral transmission. The aim of this paper is to introduce automated real-time online monitoring in the wastewater treatment plant "Ekogramont" with the possibility of using this monitoring in the prevention of the COVID-19 pandemic. The plant is located at 1080 m above sea level and was built in the period from 1998 to 1999 for the needs of the company for bottling spring water "Vlasinska ROSA", which is now owned by the company "Coca Cola" HBC. The proposed SCADA system collects the data from the sensors located in the sewage water and delivers the obtained results to the computers in the central station. The suitability of such automated monitoring comes to the fore in extreme weather conditions which prevail in this high mountain area, when for the purposes of standard analysis, wastewater sampling is disabled. The system also contains the so-called "contamination" alarm which is activated by every parameter which exceeds the set critical limit. The standard RT-PCR protocols WHO and FDA are used to detect SARS-CoV2. The detection of the viral genome in sewage, prior to the exponential phase of the epidemic, is a valuable indicator of the imminent danger of an outbreak. In this filed, modification of legal regulations in Serbia would enable the formation of a network for automated real-time monitoring of water quality control, with continuous measurement systems that would deliver the measurement results via SCADA systems to the competent institutions.