@article{MAKHILLIJSC20138321137,
    title = {Comparison Between Ant Colony and Genetic Algorithm Using Traveling Salesman Problem},
    journal = {International Journal of Soft Computing},
    volume = {8},
    number = {3},
    pages = {171-174},
    year = {2013},
    issn = {1816-9503},
    doi = {ijscomp.2013.171.174},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2013.171.174},
    author = {Zaid Ameen,Mustafa S. Khalefa and},
    keywords = {Ant colony,genetic algorithm,combinatorial optimization,traveling salesman problem,distributed algorithm},
    abstract = {The Travelling Salesman Problem (TSP) is a complex problem 
  in combinatorial optimization. The aim of this study is compare the effect of 
  using two distributed algorithm which are ant colony as a Swarm intelligence 
  algorithm and genetic algorithm. In ant colony algorithm each individual ant 
  constructs a part of the solution using an artificial pheromone which reflects 
  its experience accumulated while solving the problem and heuristic information 
  dependent on the problem. The results of comparison show that ant colony is 
  high efficient than genetic algorithm and it requires less computational cost 
  and generally only a few lines of code.}
    }