A genetic algorithm with chromosome-repairing scheme (CRS) is proposed in this paper to solve the polygonal approximation problem. Different from the existing approaches based on genetic algorithms, the proposed algorithm adopts variable-length chromosome encoding for reducing the memory storage and computational time, and develops a special crossover named gene-removing crossover for removing the redundant genes. It is known that Genetic operators may yield infea-sible solutions, and it is generally difficult to cope with them. Instead of using the penalty function approach, we propose a chromosome-repairing scheme to iteratively add the valuable candidate gene to the chromosome to deal with the infeasible solution and an evaluating scheme for the candidate genes. The experimental results show that the proposed CRS outperforms the existing approaches based on genetic-algorithms, ant-colony-optimization and tabu-search.
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