Please use this identifier to cite or link to this item:
|Title||Optimization Techniques for Solving Travelling Salesman Problem|
In the traveling salesman problem (TSP) we wish to find a tour of all nodes in a weighted graph so that the total weight is minimized. The traveling salesman problem is NP-hard but has many real world applications so a good solution would be useful. In this paper, we present several modern optimization techniques to find the shortest tour through all cities (nodes). Genetic Algorithm (GA), Simulated Annealing (SA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Bacteria Foraging Optimization (BFO), and Bee Colony Optimization (BCO) are applied on several datasets of TSP with different number of cities and different representation: distances between cities, or coordinates of cities. Each optimization technique has unique behaviors which survives it against other techniques. In this paper, the results and comparative study will present for each dataset to calculate the minimum distance and plat the resultant path.
|Published in||International Journal of Advanced Research in Computer Science and Software Engineering|
|Series||Volume: 7, Number: 3|
|Item link||Item Link|
|Files in this item|
Showing items related by title, author, creator and subject.
PID Parameters Optimization Using Bacteria Foraging Algorithm and Particle Swarm Optimization Techniques for Electrohydraulic Servo Control SystemAbo Absa, Ahmed H.; Alhanjouri, Mohammed A. (Islamic University of Gaza, 2012)Electrohydraulic servo system has been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In order to increase ...