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.

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In this article, the problem of hierarchial matrix clusterization is discussed. For this, the influence of individuals on the community was used. The problem of dividing the community into groups of related participants has been solved, an appropriate algorithm for finding the most influential community agents has been proposed. Clustering was carried out using an algorithm for reducing the adjacency matrix of a directed graph with nodes representing members of a social network and edges representing relationships between them. The applications to the problems of working groups, advertising in social networks and complex technical systems are considered.

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In modern management, one of the most popular and effective approaches to organizing activities is the creation of temporary working groups. An important indicator is the effectiveness of such groups, which strongly depends on the internal structure of the working group and the relationship between team members. For the effective functioning of the group, it is necessary that the group consists of a leader and subordinates. The artificial appointment of a team leader often proves ineffective. The article solves the problem of dividing the team into working groups, taking into account the relationship between individual personalities. Two algorithms are proposed: the first one divides the team into separate groups of possible leaders and subordinates, the second one makes effective working groups. The effectiveness of the group is calculated based on the ee efficiency function, which takes into account interpersonal relationships. Practical and numerical experiments were carried out to verify the adequacy of the model.