| Autor: |
Il-Seok Ko, Olga Yugay, Tae-Kyung Lee, Hui-Seong Na |
| Rok vydání: |
2010 |
| Předmět: |
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| Zdroj: |
Journal of the Korea Academia-Industrial cooperation Society. 11:2269-2275 |
| ISSN: |
1975-4701 |
| DOI: |
10.5762/kais.2010.11.6.2269 |
| Popis: |
The performance of Genetic Algorithms (GA) is affected by various factors such as parameters, genetic operators and strategies. The traditional approach with random initial population is efficient however the whole initial population may contain many infeasible solutions. Thus it would take a long time for GA to produce a good solution. The GA have been modified in various ways to achieve faster convergence and it was particularly recognized by researchers that initial population greatly affects the performance of GA. This study proposes modified GA with sorted initial population and applies it to solving Travelling Salesman Problem (TSP). Normally, the bigger the initial the population is the more computationally expensive the calculation becomes with each generation. New approach allows reducing the size of the initial problem and thus achieve faster convergence. The proposed approach is tested on a simulator built using object-oriented approach and the test results prove the validity of the proposed method. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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