Avoiding Premature Convergence of Genetic Algorithm in Informational Retrieval Systems
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2014, Vol 2, Issue 4
Abstract
Genetic algorithm is been adopted to implement information retrieval systems by many researchers to retrieve optimal document set based on user query. However, GA is been critiqued by premature convergence due to falling into local optimal solution. This paper proposes a new hybrid crossover technique that speeds up the convergence while preserving high quality of the retrieved documents. The proposed technique is applied to HTML documents and evaluated using precision measure. The results show that this technique is efficient in balancing between fast convergence and high quality outcome.
Authors and Affiliations
Ammar Sami Aldallal*| Ahlia University – Bahrain
Keywords
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About a discussion ‘‘Development a new mutation operator to solve the Traveling Salesman Problem by aid of genetic algorithms’’, by Murat Albayrak and Novruz Allahverdi, 2011. Expert System with Applications, 38; 3, pp. 1313–1320.
In the Short Communication published in “Expert Systems with Application” in volume 41 2014, (Comments on "Albayrak, M., & Allahverdi N. (2011). Development a new mutation operator to solve the Traveling Salesman Problem...