The planning of concert tours can be a challenging process which requires a large amount of data to be analyzed. The greatest profit cannot be obtained only by maximizing the expected number of visitors. However, most of the organizers mainly focus on that part of planning. To achieve the maximum profit possible, organizers must include other data in their analysis. Social media play a powerful role in music industry. Most of the mentioned data can be found online on social media like Facebook, YouTube or Instagram. Such data can be found in analytic sections of fan or event pages. In this paper, algorithms for tour planning have been introduced by using above mentioned data. Proposed algorithms are based on heuristic methods such as simulated annealing and genetic algorithm. A clustering based method is also implemented. Aforementioned algorithms were tested on real-world instances from Facebook fan page analytics and use number of fans and distance between cities.

A crucial part to any warehouse workflow is the process of order picking. Orders can significantly vary in the number of items, mass, volume and the total path needed to collect all the items. Some orders can be picked by just one worker, while others are required to be split up and shrunk down, so that they can be assigned to multiple workers. This paper describes the complete process of optimal order splitting. The process consists of evaluating if a given order requires to be split, determining the number of orders it needs to be split into, assigning items for every worker and optimizing the order picking routes. The complete order splitting process can be used both with and without the logistic data (mass and volume), but having logistic data improves the accuracy. Final step of the algorithm is reduction to Vehicle Routing Problem where the total number of vehicles is known beforehand. The process described in this paper is implemented in some of the largest warehouses in Bosnia and Herzegovina.

Many companies own a significant number of vehicles. To ensure the undisturbed company workflow, all vehicles have to be tracked. The standard way of vehicle tracking is via a GPS device. Sometimes, GPS devices are sending fallacious data to the server. That data can cause significant errors in daily reports or in the vehicle route preview. This paper describes an efficient technique for finding different types of anomalies in GPS data. The paper describes a connection between finding a QRS complex in ECG signal and anomalies in GPS data. The algorithm is implemented and used as a part of the GPS tracking system that is used by distribution companies in Bosnia and Herzegovina.

In real datasets often occur cases, where variable or multiple variables have unusual values. These cases are known as anomalies or outliers. For any analysis, it is essential to detect them, because they can bias the analysis. In this paper, a robust anomaly detection method is presented, and it is based on median, rather then on mean value. The method is explained, as well as its parameters and the way how they affect the results. The method is then implemented, and used on Internal Banking Payment Systems. Analysis is given and results are presented.

Two important problems distribution companies face on a daily basis are the routing and tracking of a vehicle fleet. The former is being overcome by solving the famous vehicle routing problem (VRP), a generalization of the traveling salesman problem (TSP), and the later analyses GPS data to get information of the moving vehicles. In this paper a system which uses GPS data to track the vehicles, analyze their routes and improve input data needed for the algorithm for the vehicle routing problem is described. In a real-world scenario, implementing an VRP algorithm is not enough. Algorithms which analyze GPS data ensure that the VRP algorithm takes correct input data and that the driven routes are those that the algorithm proposed.

Distribution companies use complex software systems called WMS (Warehouse Management System). The WMS is an important part of the company’s business and it can make processes simple to keep track of. Smart WMS optimizes processes to save resources and to create a more efficient working place. This paper describes the concept of a smart WMS that is implemented in one of the largest distribution companies in Bosnia and Herzegovina. The system uses artificial intelligence and optimization algorithms to improve working process. The paper describes the complete warehouse workflow that includes stock planning, initial product placement, transfer from stock to pick zone, order picking process, transport and tracking. The anomaly detection is used in some processes to improve the whole system. The main contribution of this paper is the presentation of an efficient and in the real world used smart WMS concept.

Boiler plants of different constructional design were analyseanalysed in this paper. The setting of “design” and “off-design” simulation models was performed in order to determine the impact of series of operating parameters on the geometric properties of the steam boiler furnace. Within the “design” simulation model, the setting of the simulations was performed. On the basis of these simulations, curves that describe changes of geometric parameters of the boiler furnace were obtained in relation to the given energy properties. In case of the “off-design” simulations the geometric properties were given and the energy properties were “adapted” to the given geometry. After the performed simulations, the impacts of the most important operating parameters on the geometric properties of the combustion chamber were analysed. The results obtained by this analysis could be used when designing new or in revitalization of the existing boiler plants.

A steam boiler in its original meaning is an object in which thermal energy, resulting from combustion of organic fuels, is transferred through heat surfaces to a working fluid which evaporates in the boiler with the steam further overheated to a certain temperature. steam boiler bec me more complex, in order to fulfil con demands for more efficient transformation of fuel chemical energy into thermal energy and its efficient transfer to a working fluid. With such an aim, steam boiler with additional equipment and such a complex assembly of different machines and devices connected to classical furnace and heat exchangers was named steam boiler plant. During the last decades, due to boiler plants of large capacities and high parameters with intensification and automation of all processes inside the plant, a term "steam generator" was adopted which mainly refers to large power units. Over the time, the a stant