Solving the non-linear multi-index transportation problems with genetic algorithms

In this paper we study the non-linear multi-index transporta\-tion problem with concave cost functions. We solved the non-linear transportation problem on a network with 5 indices (NTPN5I) described by sources, destinations, intermediate nodes, types of products, and types of transport, that is for...

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Bibliographic Details
Main Author: Tatiana Pașa
Format: Article
Language:English
Published: Vladimir Andrunachievici Institute of Mathematics and Computer Science 2022-02-01
Series:Computer Science Journal of Moldova
Subjects:
Online Access:http://www.math.md/files/csjm/v30-n1/v30-n1-(pp77-92).pdf
Description
Summary:In this paper we study the non-linear multi-index transporta\-tion problem with concave cost functions. We solved the non-linear transportation problem on a network with 5 indices (NTPN5I) described by sources, destinations, intermediate nodes, types of products, and types of transport, that is formulated as a non-linear transportation problem on a network with 3 indices (NTPN3I) described by arcs, types of products, and types of transport. We propose a genetic algorithm for solving the large-scale problems in reasonable amount of time, which was proven by the various tests shown in this paper. The convergence theorem of the algorithm is formulated and proved. The algorithm was implemented in Wolfram Language and tested in Wolfram Mathematica.
ISSN:1561-4042