Artificial Intelligent Systems and Machine Learning

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EAS-DTSP: An Improved Ant System Model for Dynamic Traveling Salesman (DTSP) Problem


Affiliations
1 NIMS Institute of Engineering and Technology, NIMS University, Jaipur, Rajasthan, India
2 Noble Group of Institutions, Junagadh, Gujarat, India
3 Department of Information Technology, NIMS Institute of Engineering and Technology, NIMS University, Jaipur, Rajasthan, India
     

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Ant Colony Optimization (ACO) is a novel and competitive optimization method for numerous combinatorial optimization problems. It is already applied to various optimization problems. Normally it proved best in terms of solution quality, accuracy and other parameters. This paper presents an Elitist Ant System (EAS) which uses tuning in pheromone update process to improve the performance of the basic Ant System (AS) approach. Dynamic Traveling Salesman Problem is solved in this research with the various pheromone update strategy for finding the improvements in the results. The results obtained are empirically compared with the results obtained with the basic pheromone update strategy of Ant System.

Keywords

Ant Colony Optimization, ElitistAnt System, Dynamic Traveling Salesman Problem (DTSP), Optimization.
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  • EAS-DTSP: An Improved Ant System Model for Dynamic Traveling Salesman (DTSP) Problem

Abstract Views: 228  |  PDF Views: 4

Authors

Nitesh M. Sureja
NIMS Institute of Engineering and Technology, NIMS University, Jaipur, Rajasthan, India
Ved Vyas Dwivedi
Noble Group of Institutions, Junagadh, Gujarat, India
Sanjeev Kumar
Department of Information Technology, NIMS Institute of Engineering and Technology, NIMS University, Jaipur, Rajasthan, India

Abstract


Ant Colony Optimization (ACO) is a novel and competitive optimization method for numerous combinatorial optimization problems. It is already applied to various optimization problems. Normally it proved best in terms of solution quality, accuracy and other parameters. This paper presents an Elitist Ant System (EAS) which uses tuning in pheromone update process to improve the performance of the basic Ant System (AS) approach. Dynamic Traveling Salesman Problem is solved in this research with the various pheromone update strategy for finding the improvements in the results. The results obtained are empirically compared with the results obtained with the basic pheromone update strategy of Ant System.

Keywords


Ant Colony Optimization, ElitistAnt System, Dynamic Traveling Salesman Problem (DTSP), Optimization.