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Solving Asymmetric Travelling Salesman Problem Using Group Constructive Crossover


W. K. Alrashdan1, S. Abu_owida and W. Alsharafat2


Vol. 17  No. 9  pp. 6-9


Traveling salesman Problem (TSP) is one of the important problems which classified as an NP-complete problem. Thus, this paper suggested an enhancement on Genetic Algorithm (GA) through the crossover process and its probability to optimize Asymmetric TSP (ATSP). The proposed crossover modification called Group Constructive Crossover (GCX) which used to find an optimal solution. The efficiency of the GCX is conducted by comparing it with some of existing crossover methods such as a Sequential Constructive crossover (SCX) and the ordered clustered TSP which called A Hybrid Genetic Algorithm (HGA). All comparisons were conducted by using dataset benchmark called TSPLIB.


Genetic Algorithm, Crossover, GCX, ATSP.