2. Articole
Permanent URI for this collectionhttps://msuir.usm.md/handle/123456789/17
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Item SOLVING THE NON-LINEAR MULTI-INDEX TRANSPORTATION PROBLEMS WITH GENETIC ALGORITHMS(2022) Pașa, TatianaIn this paper we study the non-linear multi-index transportation problem with concave cost functions. We solved thnon-linear transportation problem on a network with 5 in- dices (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.Item SOLVING THE NON-LINEAR MULTI-INDEX TRANSPORTATION PROBLEMS WITH GENETIC ALGORITHMS(2022) Paşa, TatianaIn this paper we study the non-linear multi-index transportation 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.Item SOLVING TRANSPORTATION PROBLEMS WITH CONCAVE COST FUNCTIONS USING GENETIC ALGORITHMS(Institutul de Matematică şi Informatică al AŞM, 2020) Pașa, TatianaIn this paper we propose a genetic algorithm for solving the non-linear transportation problem on a network with concave cost functions and the restriction that the flow must pass through all arcs of the network. We show that the algorithm can be used in solving large-scale problems. We prove that the complexity of a single iteration of the algorithm is O(nm) and converges to anǫ -optimum solution. We also present some implementation and testing examples of the algorithm using Wolfram Mathematica.