Mathematical Model to Optimize Production of Loading-Unloading Operations on the Vessel

Authors

  • Ibraim Didmanidze Batumi Shota Rustaveli State University, BSU, Batumi, Georgia, ibraimd@ukr.net
  • Givi Tsitskishvili Batumi State Maritime Academy

DOI:

https://doi.org/10.31713/MCIT.2020.08

Keywords:

hematical model, optimize production, loading-unloading operations, integer programming, linea rprogramming.

Abstract

In scientific work it is shown, that our goal is to choose the desired option from variety of alternatives (in our case different options of loading-unloading operations on the vessel) or to take decision which is the best (optimal). Classification in this case is the grounds, as taking the choice is based on choosing certain class, which can be assigned to an alternative. Stratification and rating gives us wide option to make reasonable selection, or to take a kind of decision which will be optimal for the certain moment and occasion. These methods can be used with equal strength at all stages of the processes taking place in the area of current decision making management. This refers to the object of our study of course – solution of selecting optimal option to optimize loading-unloading operation on the vessel.

It goes without saying that variety of alternatives doesn’t have any structure, thus abundance of each element was never structured randomly retrieved or no consideration has been proposed, and they are not a priority and in any order. Coming out of this it’s impossible to mention which alternative is better and which is less desirable. In order to solve the task of selecting a set of alternatives successfully, it is necessary, to make structure of the given abundance of alternatives in any form.

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Published

2020-10-22

How to Cite

Didmanidze, I., & Tsitskishvili, G. (2020). Mathematical Model to Optimize Production of Loading-Unloading Operations on the Vessel. Modeling, Control and Information Technologies: Proceedings of International Scientific and Practical Conference, (4), 29–30. https://doi.org/10.31713/MCIT.2020.08

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