ABSTRACT: The box selectivity in operational stack of container terminal is a quite common and long studied question. The pure random choice is governed by the theory of probability offering some combinatorial estimations. The introduction of operational rules like import/export separation, storage by shipping lines, sorting by rail or truck transportation etc., as well as the most notorious ‘sinking’ effect, i.e. covering of boxes arrived earlier by next cargo parties – all these blur the clear algebraiс picture and lead to appearance of many heuristic outlooks of the problem. A new impetus to this problem in last decades was given by the rapid development of IT, AI and simulation techniques. There are quite many examples of the models described in the scientific publication reflecting many real and arbitrary terminals, which embed very advanced and complicated mechanisms reflecting selected features and strategies. Unfortunately, these models usually are created ad hoc, with some pragmatic objectives and under the demand of closest possible proximity to the simulating objects. There are much less models designated to pure scientific study of the deep inner mechanisms responsible for the primal behavior of the operating container stack, enabling to introduce step by step new rules and restrictions, providing regular proving of every next stage’s adequacy and easy to use. This paper describes one attempt of this kind to create a new theoretical tool to put into the regular toolkit of the container terminal designer. The study starts with mathematical (combinatorial) considerations, proceeds with some restrictions caused by physical and technological characteristics, and ends up with the simulation model, which adequacy is confirmed by practical results.

KEYWORDS: Cargo Handling, Container, Simulation Model, Artificial Intelligence (AI), Box Selectivity, Cargo Handling System, Container Cargo-Handling System, Theoretical Selectivity

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