EVOLUTIONARY ALGORITHM BASED ON SIMULATED ANNEALING FOR THE MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS

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Autor principal: Elias D. Nino Ruiz
Formato: Artículo científico
Lenguaje:en
Publicado: International Journal of Combinatorial Optimization Problems and Informatics 2013
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author Elias D. Nino Ruiz
author_facet Elias D. Nino Ruiz
contents EVOLUTIONARY ALGORITHM BASED ON SIMULATED ANNEALING FOR THE MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS Elias D. Nino Ruiz Henry Nieto Parra Anangelica Isabel Chinchilla Camargo Computación Multi Genetic Algorithms Simulated Annealing objective Optimization Combinatorial Optimization This paper states a novel hybrid-metaheuristic based on the Theory of Deterministic Swapping, Theory of Evolution and Simulated Annealing Meta-heuristic for the multi-objective optimization of combinatorial problems. The proposed algorithm is named EMSA. It is an improvement of MODS algorithm. Unlike MODS, EMSA works using a search direction given through the assignation of weights to each function of the combinatorial problem to optimize. Also, in order to avoid local optimums, EMSA uses crossover strategy of Genetic Algorithm. Lastly, EMSA is tested using well know instances of the Bi-Objective Traveling Salesman Problem (TSP) from TSPLIB. Its results were compared with MODS Metaheuristic (its precessor). The comparison was made using metrics from the specialized literature such as Spacing, Generational Distance, Inverse Generational Distance and Non-Dominated Generation Vectors. In every case, the EMSA results on the metrics were always better and in some of those cases, the superiority was 100%. 2013 artículo científico 2007-1558 https://www.redalyc.org/articulo.oa?id=265229633005 en http://www.redalyc.org/revista.oa?id=2652 International Journal of Combinatorial Optimization Problems and Informatics application/pdf International Journal of Combinatorial Optimization Problems and Informatics International Journal of Combinatorial Optimization Problems and Informatics (México) Num.2 Vol.4
format Artículo científico
id redalyc_265229633005
institution Redalyc
language en
publishDate 2013
publisher International Journal of Combinatorial Optimization Problems and Informatics
spellingShingle EVOLUTIONARY ALGORITHM BASED ON SIMULATED ANNEALING FOR THE MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS
Elias D. Nino Ruiz
Computación
Multi
Genetic Algorithms
Simulated Annealing
objective Optimization
Combinatorial Optimization
EVOLUTIONARY ALGORITHM BASED ON SIMULATED ANNEALING FOR THE MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS Elias D. Nino Ruiz Henry Nieto Parra Anangelica Isabel Chinchilla Camargo Computación Multi Genetic Algorithms Simulated Annealing objective Optimization Combinatorial Optimization This paper states a novel hybrid-metaheuristic based on the Theory of Deterministic Swapping, Theory of Evolution and Simulated Annealing Meta-heuristic for the multi-objective optimization of combinatorial problems. The proposed algorithm is named EMSA. It is an improvement of MODS algorithm. Unlike MODS, EMSA works using a search direction given through the assignation of weights to each function of the combinatorial problem to optimize. Also, in order to avoid local optimums, EMSA uses crossover strategy of Genetic Algorithm. Lastly, EMSA is tested using well know instances of the Bi-Objective Traveling Salesman Problem (TSP) from TSPLIB. Its results were compared with MODS Metaheuristic (its precessor). The comparison was made using metrics from the specialized literature such as Spacing, Generational Distance, Inverse Generational Distance and Non-Dominated Generation Vectors. In every case, the EMSA results on the metrics were always better and in some of those cases, the superiority was 100%. 2013 artículo científico 2007-1558 https://www.redalyc.org/articulo.oa?id=265229633005 en http://www.redalyc.org/revista.oa?id=2652 International Journal of Combinatorial Optimization Problems and Informatics application/pdf International Journal of Combinatorial Optimization Problems and Informatics International Journal of Combinatorial Optimization Problems and Informatics (México) Num.2 Vol.4
title EVOLUTIONARY ALGORITHM BASED ON SIMULATED ANNEALING FOR THE MULTI-OBJECTIVE OPTIMIZATION OF COMBINATORIAL PROBLEMS
topic Computación
Multi
Genetic Algorithms
Simulated Annealing
objective Optimization
Combinatorial Optimization
url https://www.redalyc.org/articulo.oa?id=265229633005