Model and algorithm for calculating the probability characteristics of the storage and processing of refrigerating containerized cargoes

To describe the capacity of container terminals, the deterministic methods, leading to large allowances in the calculations, were previously used. These methods do not reflect the specifics of processing and storage of refrigerated cargo: the time interval between the time of the request to the service and its response is not of a random nature, however, the time of delivery of parts of container cargo to the terminal is a random flow of events. In the considered system of mass service of the open multichannel type, which receives irregular homogeneous or inhomogeneous flow of orders with unbounded standby time, the main task is to calculate the waiting time for the containers for safekeeping. To find this option, the process occurring while handling the containerized refrigerating cargoes in terminals, — a discrete type process with a finite (or countable in general) set of the states should be examined. As a set of states, a change in the number of shipments that are in the queue for processing is taken. The considered processes of shipments transfer from one state to another at the moment, when a new shipment arrives or one of the conditionally functional sections is released. For the development of the mathematical model a private theorem on the repeated tests, the Newton binomial expansion to the series and the law of the Poisson distribution were used. To describe the probabilities of individual states the Bayes' theorem is used. The system is subject to the following features of the flow requirements: ordinary, stationary and without after-effects. The system is considered by the example of operating the container terminal, having conditionally functional sections with a certain duty cycle, which takes irregular and uniform flow of the vessels with the resultant intensity. The system allows optimizing such factors as equipment downtime, excess of places in warehouses, queuing and possibility of accounting random variables (time of arrival of the shipment and cargo processing time interval).