Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

• Autores: Escobar Z., Antonio H.; Gallego R., Ramón A.; Romero L., Rubén A.
• Tipo de recurso: Article of journal
• Fecha de publicación: 2011
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/33479
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/33479; http://bdigital.unal.edu.co/23559/; http://bdigital.unal.edu.co/23559/2/; http://bdigital.unal.edu.co/23559/3/
• Palabra clave: planeamiento de redes de transmisión; algoritmos genéticos; algoritmos heurísticos constructivos; metaheurística; población inicial.; electricity distribution network expansion planning; genetic algorithm; constructive heuristic algorithm; met heuristics; initial population.
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional