A modified multiple-searching method to genetic algorithms for solving traveling salesman problem

This paper proposes a new method of a modified multiple-searching genetic algorithm (MMGA) for solving traveling salesman problems (TSPs). The proposed approach can find the optimal solutions quickly via different search strategies. We also show that running a genetic algorithm with a modified multiple-searching mechanism from solutions to similar TSP problems can lead to better performance than the traditional GAs, immune genetic algorithms, and our previous MGA. Moreover, our proposed algorithm can not only easily combine other excellent modified GAs but also apply to other optimization problems. The analysis results show our algorithm is robust and can produce better solutions more quickly.