Multi-Objective Optimal Solution Search based on Genetic Algorithms
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MUNTEANU, Silvia, TSURKAN, Ana, ALEXEI, Victoria, SUDACEVSCHI, Viorica, ABABII, Victor, CĂRBUNE, Viorel, BORDIAN, Dimitrie. Multi-Objective Optimal Solution Search based on Genetic Algorithms. In: Electronics, Communications and Computing, Ed. 12, 20-21 octombrie 2022, Chişinău. Chișinău: Tehnica-UTM, 2023, Editia 12, pp. 247-252. DOI: https://doi.org/10.52326/ic-ecco.2022/CE.07
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Electronics, Communications and Computing
Editia 12, 2023
Conferința "Electronics, Communications and Computing"
12, Chişinău, Moldova, 20-21 octombrie 2022

Multi-Objective Optimal Solution Search based on Genetic Algorithms

DOI:https://doi.org/10.52326/ic-ecco.2022/CE.07

Pag. 247-252

Munteanu Silvia, Tsurkan Ana, Alexei Victoria, Sudacevschi Viorica, Ababii Victor, Cărbune Viorel, Bordian Dimitrie
 
Technical University of Moldova
 
Proiecte:
 
Disponibil în IBN: 3 aprilie 2023


Rezumat

The paper presents the results of research carried out to solve complex problems aimed at the efficient use of natural and energy resources. The objectives of the paper are achieved by identifying the control process based on a Multi-Agent system with distributed data processing that implements a Multi-objective optimal solution search model based on the application of a Genetic Algorithm with Collective Computation. The set of Agents presents a computational architecture that forms a structured network topology based on a P-Systems model presented in the form of a Venn diagram. The Object diagram and the Venn diagram of the P-Systems model are presented in the paper. The correctness of the developed models was verified on the basis of a control system of the artificial lighting process that provides for the minimization of energy consumption, while ensuring the quality of the lighting process.

Cuvinte-cheie
Multi-Objective Optimization, genetic algorithms, p-systems, Multi-Agent system, Sensor Network, distributed computing, collective computing