Solving traveling salesman problem using cuckoo search and ant colony algorithms

Abstract EN

Optimization is a method that is used from economic to design.

The best tools available are very important to be utilities .when there is some randomize nature value that's depend in the algorithm is called stochastic.

Algorithm with stochastic partitions are often named heuristic or meta heuristic recently.

Traveling salesman problem (TSP)is hard a combinatorial optimization problem that leads to find the best tour for the person .

this problem can be applicator in many different area such as DNA fragments, planning and logistics.

There are many algorithm that is used to solve this problem.

In this paper, Ant colony optimization (ACO) is the first algorithm that is applied which depending on the ant colonies law for finding the best tour of TSP .

The other algorithm that is performed, is cuckoo search (CS) that satisfy the law of brood parasitism of some cuckoo specie to find the best tour of the same problem.

Compare between two algorithms of meta heuristic for six cities with different parameter's value to evaluate the result .

conclude that the CS performance is better than ACO with speed convergence.