350 rub
Journal Science Intensive Technologies №3 for 2010 г.
Article in number:
Using fuzzy sets and systems for vessel-s subsystems optimization
Authors:
T. G. Artyushina
Abstract:
The mathematical model of a vessel is a multitier object that has predefined global goal for a system and goals for every subsystem. In other words, this mathematical model represents a vessel as a sophisticated technical system. The problem of optimization using above described mathematical model comes to the set of smaller optimization problems that are later solved and matched to the requirements of a vessel. Let-s clarify how this mathematical tool can be used for multitier system called «the vessel». The sophisticated system «the vessel» breaks down into subsystems. Therefore, the global problem of optimization becomes a number of local smaller interrelated optimization problems. It-s important to remember that any optimal solution for a subsystem that we-ve found has to match optimal solutions of all the other subsystems of the vessel. The central (top) system is «the vessel», the low level systems - subsystems «Hull», «freight», «steering arrangement», «power plant», «cargo equipment», «hydrodinamical complex», etc. There are functional limitations, optimizing variables and efficiency criteria for every subsystem. The most important criteria in the ship development is its cost. There are several major constants in our example: freight-carrying capacity, specific capacity, full speed, cruising range, endurance of ship, crew size, a number of screw propellers, and the coefficient of superstructure. In addition there are parameters that describe the economical efficiency: the length of the service range, and also costs: 1 t of metal case, 1 t of hull equipment, 1 t of fuel. Fuzzy logic allows us to solve the problem of optimizing the sophisticated multitier system. In this article we proved that it-s possible to match optimal solutions of subsystems as well as effectively optimize the multitier system.
Pages: 53-57
References
  1. Артюшина Т.Г., Гайкович А.И. Проблема повышения эффективности проектирования судов на  исследовательских стадиях с использованием САПР. Судостроение. 2007. №5. С. 11 - 14.
  2. Zadeh L.A. Fuzzy Sets // Information and Control. 1965. V. 8. P. 338-353.
  3. Беллман Р., Заде Л. Принятие решений в расплывчатых условиях // В сб.: Вопросы анализа и процедуры принятия решений. М: Мир. 1976. С. 172-215.