A dissertation entitled The optimization of harbour transshipping processes via system dynamics has multiple goal functions and represents a demanding task, because the load transshipping system is considered a highly complicated task. Its scientific research requires suitable and new scientific methods, including the system dynamic simulation modeling. The system approach in solving scientific and professional problems is getting yet more important, and the methodology of system researches constitutes the basis of the scientific researches applied in this dissertation. The reasons for the growing interest in the scientific research problems are made clear enough and are repeatedly indicated in the literature. One of the most important postulates relies on the fact that in practically every sphere of human action (science, education, technics, manufacturing, management, etc.), people do not encounter isolated objects, things, processes of phenomena, but their complicated interrelated complexes which, in fact, represent different kinds of systems. The task of such system research has inevitably lead to the occurrence of a methodological problem of such a research, which practically means that the given research problem, in order for it to be treated in the light of the system approach, is identified as a system. In that way, the emersion of cybernetics – a science whose research subject is studying managing complex dynamic systems - has conditioned the finding of a new suitable scientific method. The main goal of this dissertation is to provide an overview of theoretical methods, models, techniques and tools used in science and in direct practice for the modern management of harbour systems, as well as to give adequate recommendations for advancing harbour resource management. There are two basic techniques in solving problems when it comes to deciding on the management of transshipping processes, and they are optimization and simulation. The first one, optimization, involves approaches and methods that belong to mathematical programming. The other technique, simulation, is mathematically less rigorous than the first one, and best determines all the methods that, organized, examine the possibilities and search for optimal solutions of the given assignments, without precisely predetermined criteria for the termination of the searching process. Since both techniques, individually as well as mutually, have their advantages and shortcomings, one of the advancement directions of the area of machine aided deciding on shipping management is concentrated on incorporating these techniques. That is, it is focused on building such approaches in mathematical modeling of complex problems, which will take advantage of these techniques and, at the same time, decrease their individual shortcomings. The optimization area relies on a great number of advanced software applications that integrate sophisticated mathematical algorithms and modeling techniques with an intelligent software programming and the ability of data processing. These techniques are intelligent agents, Soft computing, Soft computing techniques (fuzzy, neural networks, genetic algorithms), and gradient methods. The result of research is also a simulation model dedicated to the problem of combinatory, i.e. global optimization. It is not hard to conclude that the same software can be adjusted to different needs, so it can be said that the field of possible appliance of findings is implemented in almost all shipping management domains.