DETERMINATION OF THE OPTIMAL RATIO OF TYPES OF PORT EQUIPMENT WHEN WORKING WITH CONTAINERS IN THE OPERATIONAL AREA OF A CARGO TERMINAL OF A SEA PORT

Abstract

In this work, one of the dynamic programming methods is used to solve the problem of determining the dominant sequence of using combinations of port equipment in the implementation of production processes with container cargo flow in the corresponding zone of the port container terminal. The production zones of the container port terminal are taken into account. Compliance of the area of the storage area with the current regulations has been established. Defined types of containers. The existing methods of storing large-tonnage containers at the storage area of the operational zone of the port's container terminal were determined, and the longitudinal-transverse type of storage was selected for consideration. A "line" of port equipment for this type of production has been installed. The types and combinations of port cargo equipment that can be used at the selected facility are defined. Among the proposed indicators of the efficiency of using a set of port equipment for the further solution of the problem, the indicator of operating costs and the indicator of ship productivity were selected. The range and alternative strategies of port equipment are defined in accordance with their combinations. The limited ranges of their application are established. The corresponding derived, admissible and working data sets were formed for the implementation of the method of determining the dominant sequence of the use of combinations of port equipment in the implementation of production processes with container cargo flow in the corresponding zone of the port container terminal using the proposed Kettel algorithm. Restrictions have been introduced on indicators of the efficiency of the use of the totality of port equipment and time indicators. As a result, dominant sequences of combinations of port equipment were determined, one of which is a priority according to the established restrictions. It is shown that the proposed approach can be used for other modeling and optimization configurations. The actualization of further integration of compositions and combinations of derived data is substantiated.