INTRODUCTIONSignificant increase in the world container trade over the past two decades has resulted in an increased capacity of container ships [1] and the capacity together with throughput of ports container terminals. This encourages the development of ports, primarily port equipment, technology, information and communication systems. The requirements for capacity expansion, investments in infrastructure and transport entities, reducing the negative environmental impact, and customer requirements for faster, more efficient and cheaper transportation of goods has become a product for new transport solutions development [3,4,5].Similarly, ports are faced with changes in their operations. Shippers require fast and efficient handling and reduction of container ships detention. This implies expansion of port capacity and implementation of new equipment, and high-quality connections to the hinterland. Additional requirements for fast and high-quality shipping to customers represents a major financial, organizational and operational requirement to which not all the world ports can respond.Changes in the present transport chain lead to the development of inland terminals. Inland terminals disburden port capacity on the one hand and on the other hand they become a competitive advantage for the less developed ports. This allows them better connections with the hinterland, directly attracting additional cargo. Inland terminals become an additional link in the present transport chain, while the use of intermodal transport technology enables acceleration of transport processes reducing the total transport costs. In the present transport chain, there have been changes in the mode of shipment from the manufacturer to the port and from the port to the end users (Figure 1). TOMISLAV ROŽIĆ, Ph.D. 1

With certainty, we can say that we are in the process of a new big revolution that has its name, Big Data. Though the term was devised by scientists from the area such as astronomy and genomics, Big Data is everywhere. They are both a resource and a tool whose main task is to provide information. However, as far as it can help us better understand the world around us, depending on how they are managed and who controls them, they can take us in some other direction. Although the figures that bind to Big Data can seem enormous at this time, we must be aware that the amount of what we can collect and the process is always just a fraction of the information that really exists in the world (and around it). However, from something we have to start!

Raising the service level and developing new logistic services require better understanding of logistic processes and possibilities of optimization. Different methodologies have been used for that purpose, while the application of Business Process Management (BPM) methodology is outlined in this paper. Identifying parts of logistic processes that could be optimized is facilitated by applying BPM methodology. It also enables more accurate quantification of impacts of the changes introduced in a particular process or activity on the processes as a whole and to other interacting processes. The application of BPM methodology is demonstrated in the case study, where a solution for logistic processes optimization is suggested and the prospective outcomes are simulated. The results of the logistic process comparative analysis have indicated a synergic effect of different improvements in sub-process on the effectiveness of the process as a whole, both on the operative and managerial level. The respective changes in workload distribution among interacting logistic processes have been quantified according to the same methodology.

In this paper the problems of locating urban logistic terminals are studied as hub location problems that due to a large number of potential nodes in big cities belong to hard non-polynomial problems, the so-called NP-problems. The hub location problems have found wide application in physical planning of transport and telecommunication systems, especially systems of fast delivery, networks of logistic and distribution centres and cargo traffic terminals of the big cities, etc. The paper defines single and multiple allocations and studies the numerical examples. The capacitated single allocation hub location problems have been studied, with the provision of a mathematical model of selecting the location for the hubs on the network. The paper also presents the differences in the possibilities of implementing the exact and heuristic methods to solve the actual location problems of big dimensions i.e. hub problems of the big cities.

Logistics and distribution centres represent very significant infrastructure elements of the macro-logistic system. The creation of the logistics and distribution centres and their connection into a wide (global) network have resulted in the creation of conditions for an adequate distribution of labour and significant increase in the productivity of all the logistics elements and processes, noting that the logistics and distribution centres in this concept have a superregional significance. This paper represents the summary (results) of the research that was carried out on a large number of logistics and distribution centres with the aim of considering the complexity and the issues related to the logistics and distribution centres and the distribution network, their elements and action of the subsystems according to the following criteria: spatial, technical, technological, and organizational, with the aim of defining the categorisation model of the logistics and distribution centres. The analysis of the selected data collected during the research has resulted in defining of the categorisation model of the logistics and distribution centres which foresees six categories. Each of the foreseen categories has been defined according to the set model by the mentioned traffic, technical and technological, and organisational characteristics and the level of service. This is precisely where the application of the categorisation model of the logistics and distribution centres can be found, which will define the relevant categories of the centres applicable in the creation of effective distribution