The shipping market is an economic derivative of global production and trade, being precariously subject of their cyclic changes, depressions and expansions. This paper analyses the condition of global container shipping market, caused by long-lasting economic and financial crisis that begun in 2008, but is still much visible within the container industry, particularly through overcapacity and low freight rates. It also deals with major changes of maritime container carrier’s management strategies, development and application of advanced transportation, technological, technical, economical, organizational and commercial measures in order to adapt and cope with new business environment. Finally, an attempt is made to forecast the market, potential difficulties and to propose problem-solving measures.

The container shipping industry market is very dynamic and demanding, economically, politically, legally, and financially. Considering the high cost of core assets, ever rising operating costs, and the volatility of demand and supply of cargo space, the result is an industry under enormous pressure to remain profitable and competitive. To maximize profits while maintaining service levels and ensuring the smooth flow of cargo, it is essential to make strategic decisions in a timely and optimal manner. Fleet deployment selection, which includes the profile of vessel hire, as well as their capacity and port rotation, is one of the most important strategic and tactical decisions container shipping operators must make. Bearing in mind that maritime business is inherently stochastic and uncertain, the key aims of this paper are to address the problem of fleet deployment under uncertain operating conditions, and to provide an integrated and optimized tool in the form of a mathematical model, metaheuristic algorithm, and computer program. Furthermore, this paper will show that the properties of the provided solutions exceed those offered in the literature so far. Such a solution will provide the shipping operator with a decision tool to best deploy its fleet in a way that responds more closely to real life situations and to meet the maximum demand for cargo space with minimal expense. The final goal is to minimize the operating costs while managing cargo flows and reducing the risks of unfulfilled customer demands.