• Balraj Singh
• Er. Harpreet Kaur

Ant Colony Optimization (ACO) algorithms are motivated by the searching behavior of ants in nature. The research paper focuses on the working principle of ACO with a special condition of obstacles been placed between the starting point (source) and the food source (destination). The optimization code has been implemented using MATLAB with three obstacles placed between source and destination. The implementation has been performed with three different cases with a varying number of iterations to calculate the Best Cost in each case.

Ants, Ant Colony Optimization, Best Cost, Best Path, obstacles.

" Improving Best Cost in Ant Colony Optimization with obstacles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.1039-1051, May-2019, Available :http://www.jetir.org/papers/JETIR1905S56.pdf

" Improving Best Cost in Ant Colony Optimization with obstacles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp1039-1051, May-2019, Available at : http://www.jetir.org/papers/JETIR1905S56.pdf