Volume 5, Issue 4, August 2017, Page: 57-64
Two-Level Multi-criteria Model for Calculating Multinomenclature Spare Parts of an Auto Service Enterprise Based on the Rougher Algorithm for Optimizing the Behavior of Their Particles
Karimov Nijat Ashraf, Department of Automotive Engineering, Azerbaijan Technical University, Baku, Azerbaijan
Dyshin Oleq Aleksandr, Department of Applied Mechanics, Azerbaijan State University of Oil and Industry, Baku, Azerbaijan
Gozalov Sulhaddin Kamal, Department of Automotive Engineering, Azerbaijan Technical University, Baku, Azerbaijan
Received: Aug. 29, 2017;       Accepted: Sep. 18, 2017;       Published: Nov. 8, 2017
DOI: 10.11648/j.sr.20170504.12      View  1473      Downloads  37
Abstract
On the example of the two-criterion problem with the objective functions of the maximum, the confidence probabilities of the demand and the minimum of the total costs show the applicability of the method of Vector Optimization of Particle Swarm Optimization (VEPSO). Compared with genetic algorithms and other methods of evolutionary modeling, this method is easy to implement and has high efficiency, as well as the accelerated cost of an approximate solution of the problem from the external archive of the no dominant best solutions to the Pareto front, which is the boundary of the Pareto-optimal Compromise) solutions.
Keywords
Rougher Algorithm, Swarm Optimization, Vector Optimization of Particle Swarm Optimization (VEPSO)
To cite this article
Karimov Nijat Ashraf, Dyshin Oleq Aleksandr, Gozalov Sulhaddin Kamal, Two-Level Multi-criteria Model for Calculating Multinomenclature Spare Parts of an Auto Service Enterprise Based on the Rougher Algorithm for Optimizing the Behavior of Their Particles, Science Research. Vol. 5, No. 4, 2017, pp. 57-64. doi: 10.11648/j.sr.20170504.12
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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