In a modern economy, international trade is an important factor in the development of various regions. Shipping is one of the most important elements of the global supply chain. However, after the economic crisis of 2008, global shipping revenues plummeted. One way to restore profitability is the consolidation of shipping routes and the globalization of shipping lines. As container transport lines move to larger ships, the structure of the delivery route becomes a structure with intermediate points. This trend put forward higher demands on the port infrastructure, which aggravated the competition between regional ports, as well as ports that could degrade into a large cargo consolidation port. The economic advantage is enhanced by cooperation between shipping lines and ports. Thus, ports and shipping lines in the same supply chain can be mutually beneficial partners. The study analyses the effectiveness of horizontal and vertical cooperation between ports and carriers. As a source of information, a review of the literature on this issue, expert opinions, and statistical data is taken. Next, a mathematical model is built on the basis of cooperative game theory, and numerical analysis is carried out. The results show that the strategy of cooperation of shipping lines strongly depends on the situation with the supply and demand of vessels. A port that interacts with shipping lines will significantly reduce port charges, which creates the advantage of receiving more port requests. However, cooperation may lead to losses for the port, so a redistribution of profits is necessary to maintain the coalition.

This paper consideres the problem of multi-criteria optimization. Two approaches to this problem are presented. The first method uses the idea of weight center. The second method is based on cooperative game theory in multi-criteria choice. The Shapley value is used as a weight vector for assessment of solutions. As an example a complex energy system is analyzed.

The dynamics of Alzheimer’s disease spread in aging groups of population are described using an Inflow-Outflow Model. This article presents the results of a retrospective forecast of non-stationary dynamics for key indicators of the spreading process, based on constructing linear trends of the stochastic rates of change in the integral volumes of inflow and outflow. The novelty of the proposed methodology is threefold: (1) it introduces a novel approach to modeling non-stationary time series for non-communicable diseases by shifting the focus to the stochastic dynamics of accumulated case volumes rather than volatile annual figures; (2) it identifies and operationalizes for forecasting the property of a monotonic decrease in the rates of the integral inflows and outflows within the prevalence process; and (3) it develops and tests a practical forecasting technique based on extrapolating linear trends of these rates. To demonstrate the model’s effective- ness, sample retrospective 10-years forecasts developed in 2005, 2010, and 2015 are presented for the World and some regions. The MAPE values for 10-years forecasting windows belongs to the interval [0.23%;2.73%], and MAPE values are in the interval [0.08%;0.75%]. The article also provides a long-term projection of disease prevalence to 2050 using a model-based forecasting approach.