• Md. Borhan Uddin
• Taki Uddin

Producing optimal tours in linear time through human subjects one of the most intensively studied problems in the area of optimization and the Traveling Salesman Problem (TSP) is a popular example of such optimization. The performance of TSP can be modeled by a graph, matrix, and different types of algorithms. The most frequently seen TSP problems are computer wiring, vehicle routing, job sequencing, combinatorial data analysis. The optimization problem of TSP is to find the salesman’s route from a specific location and back, where each city will be visited once. If there are fewer cities then it is easy to solve and the complexity increases exponentially as the number of cities increases. The total distance and cost of other resources incurred should all be minimum. Our paper addresses the Constraint Satisfaction Problem (CSP) in TSP using Depth-First Search (DFS) and Genetic Algorithm (GA) to find a better solution and comparing the efficiency of both algorithms. Our result shows the GA performs better at solving TSP compared to DFS.

algorithms, constraint satisfaction problem, traveling salesman problem, genetic algorithm, depth first search

"Solving Constraint Satisfaction Problem in TSP using GA and DFS algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.417-421, November-2020, Available :http://www.jetir.org/papers/JETIR2011343.pdf

"Solving Constraint Satisfaction Problem in TSP using GA and DFS algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp417-421, November-2020, Available at : http://www.jetir.org/papers/JETIR2011343.pdf