Optimization Problems And Genetic Algorithms
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Keywords
genetic algorithms, optimization, traveling salesman problem (TSP)
Abstract
This paper presents an application of genetic algorithms (GAs) to a well-known traveling salesman problem (TSP) which is a challenging optimization task. Using the techniques of selection, crossover, and mutation borrowed from the Darwin’s evolution theory, GAs were able to find the optimal solution after generating only 24 populations of solutions instead of exploring more than a million possible solutions.
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