NEW CROSSOVER VIA HYBRID ANT COLONY SYSTEM WITH GENETIC ALGORITHM AND MAKING STUDY OF DIFFERENT CROSSOVER FOR TSP

The traveling salesman problem (TSP) is a very famous NP-hard problem in computer science and operations research. In this study, proposed a new hybrid crossover (SPMX) combining the shuffle crossover and partially mapping crossover which served to develop Genetic algorithm (GA) to solve this problem since crossover is the main component of GA. And, apply the proposed SPMX on hybrid ant colony system with GA with Ant colony system (ACS), which called by (ACSGA) to solve TSP. Experimental results on some well-known TSPLIB instances of different types and sizes. The obtained comparative study clearly demonstrates the utility of the proposed a (SPMX) to enhance ACSGA for resolving TSP and the distance decrease by 0.82% with average 0.47%.