Abstract
Genetic algorithm tries to find the optimized solution with different process stages. All stages are inspired by the natural mechanisms with the genes as individuals. Modelling that natural loop in Computer systems to find the optimized populations which is various combinations of genes, provide a good method to find a solution for problems that can’t solve with any mathematical definition. Today, genetic algorithm is using for diverse fields like path finding, robotic, medical, network, big data and so more. In this work, genetic algorithm improved for path finding methods. All stages are examined and discussed to find possible improvements. A new step which is called as “Fate Decide Operator” is implemented and compared with traditional genetic algorithm. Fate decide algorithm’s tests shows that the fate decide operator has some advantages for path finding algorithms. Improved genetic algorithm can be used in various problems.
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Zengin, H.A., Işik, A.H. (2020). Improvement for Traditional Genetic Algorithm to Use in Optimized Path Finding. In: Hemanth, D., Kose, U. (eds) Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-36178-5_37
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DOI: https://doi.org/10.1007/978-3-030-36178-5_37
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