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Problem Solving of graph correspondence using Genetics Algorithm and ACO Algorithm

Alireza Rezaee, Azizeh Ajalli

In this paper, new genetics and Ant colony optimization algorithm for solving the problem of graph correspondence is presented. When using the genetics technique for the problem of graph correspondence, it is not easy to define the crossover operator. our attempt will be to present a definition holding the integration of the population graph in a one-to-one correspondence. we present new and suitable definitions for the target function and a function giving score to a solution at the end of any cycle. We compare both algorithms and try to find their advantages and their shortcomings.