Open AccessPARAMETRIC SYNTHESIS ALGORITHMS IN THE DESIGN OF FLEXIBLE MANUFACTURING SYSTEMS BASED ON COMPUTER MODELING
Author(s) -
А. И. Сергеев,
S.E. Krylova,
S.Yu. Shamaev,
T.R. Mamukov
Publication year - 2021
Publication title -
izvestiâ samarskogo naučnogo centra rossijskoj akademii nauk
Language(s) - English
Resource type - Journals
ISSN - 1990-5378
DOI - 10.37313/1990-5378-2021-23-2-106-114
Subject(s) - genetic algorithm , automation , algorithm , parametric statistics , computer science , convergence (economics) , mathematical optimization , process (computing) , production line , production (economics) , parametric model , engineering , mathematics , mechanical engineering , statistics , economics , macroeconomics , economic growth , operating system
The article discusses an approach to the automation of parametric synthesis of production equipment of highly automated production systems. Three optimization methods are considered: the coordinate descent method based on the golden ratio, the Hook-Jeeves method, and the genetic algorithm. With the help of the considered methods, a computational experiment was carried out aimed at finding the design parameters of a flexible manufacturing system that are optimal according to the criterion of equipment loading. The design parameters were assessed on the basis of a computer model of the production equipment operation process. The analysis of the experimental results showed that the highest efficiency of determining the global optimum was obtained using the genetic algorithm, but its operation takes the longest time. It has been suggested that it is possible to reduce the search time by studying the effect of the mutation value, which does not allow the genetic algorithm to get stuck in the local optimum, but worsens the convergence of the solution.